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AI Observability

Braintrust

Braintrust evaluates and traces AI apps and agents. Dataset experiments and scorers test prompt and model changes, plus code, before release. Production tracing and online scoring, plus Topics, track results afterward. It runs in Braintrust's US or EU cloud, or, on Enterprise, with a data plane in your own cloud.

The 30-Second Take

Pick Braintrust if evals should gate every prompt, model and code change.

A failing production trace becomes a dataset example that code, an LLM judge or a person scores every later change against. Dropbox blocks merges on about 150 judged queries per pull request.

Best fit
Product teams shipping LLM features that want evals to gate every prompt and model change.
Main constraint
Braintrust charges per gigabyte ingested and per score recorded, and nothing caps the total. BYOC and self-hosting require Enterprise.
First move
Instrument one feature on Starter. Build a ten-example dataset from real traces and run it in CI on every pull request.

Why

Watch the keys: in May 2026 an attacker reached a backup holding decrypted provider keys, and 30 customers reported suspicious key use. Connect providers through short-lived credentials and set spend alerts, since nothing caps the bill.

Practitioner sentiment, teams and leaders+50 Strong positive

32 practitioners, 73 sources reviewed, Updated Oct 30, 2026How this is measured

Read the GILD Review
Save a product your organization uses.Keep up with Braintrust without adding it to your stack.Visit Website
Operating stack
AI Application Platform

Comparisons

How does Braintrust compare with the alternatives?

See all 5 comparisons

  1. Braintrust vs LangSmith

    • AI Observability

    On Parlance Labs' 100 production traces, Braintrust Loop found the most failures and LangSmith Engine too few to score. Pick Braintrust for evals many people review, US$474 a month at 200,000 traces in GILD's calculation; pick LangSmith to host LangGraph agents too.

  2. Braintrust vs Langfuse

    • AI Observability

    CREATE SOMETHING retired Braintrust for Langfuse in July 2026. Pick Langfuse to self-host its MIT-licensed core free; at 200,000 traces a month GILD's calculation puts Langfuse Pro at US$369 and Braintrust Pro at US$474. Pick Braintrust for a managed eval product whose data plane runs in your cloud only on Enterprise.

  3. Braintrust vs Arize

    • AI Observability

    On Parlance Labs' 100 production traces, Braintrust Loop caught the most failures and 91% of Arize Alyx's flags were valid. Pick Arize to self-host free on Phoenix; pick Braintrust for Pro overage rates you can price, US$474 a month at 200,000 traces in GILD's calculation.

Operator Insights

What are teams learning from building on Braintrust and running it in production?

See all 12 operator accounts

Buying and deployment

What a team building on it should verify before production traffic grows.

Sourced from Braintrust documentation

How you buy it

US$249

A month for Pro with 5 GB and 50,000 scores. Starter is free with 1 GB.

Source 1, braintrust.dev, Pricing: PricingSource 2, Braintrust, Plans and limits: Plans and limits

Details

Starter costs US$0 monthly for 1 GB of processed data and 10,000 scores, with 14-day retention and US$10 in model credits. Pro costs US$249 for 5 GB and 50,000 scores, with 30-day retention and US$100 in credits. Every plan has unlimited users. Enterprise pricing is custom, invoiced annually.

Cost drivers

US$3 per GB

Past the Pro allowance, counted at ingestion, so deleting data does not lower it.

Source 1, braintrust.dev, Pricing: PricingSource 2, Braintrust, Plans and limits: Plans and limitsSource 5, Braintrust, Monitor usage and spend alerts: Monitor usage and spend alerts

Details

Above the allowance, processed data costs US$4 per GB on Starter and US$3 on Pro. Scores cost US$2.50 and US$1.50 per 1,000, respectively. Braintrust counts data at ingestion, so deletion does not reduce that charge. Extending Pro retention up to 180 days costs US$0.50 per GB per month. Spend alerts do not stop usage.

Where it runs

US or EU, fixed

Pick the data plane when you create the organization. Enterprise adds BYOC or self-hosting.

Source 6, braintrust.dev, Organizations and data plane region: Organizations and data plane regionSource 3, Braintrust, Deployment options: Deployment optionsSource 7, braintrust.dev, Self-hosting Braintrust: Self-hosting Braintrust

Details

Choose a US or EU data plane when creating the organization. That choice is fixed. Enterprise adds vendor-operated BYOC in your cloud account or a self-hosted data plane on AWS, GCP, or Azure. Braintrust always hosts the control plane, including login and the UI, plus project metadata.

What to verify

May 2026

An attacker reached stored provider keys in a backup. Federated identity is now supported.

Source 8, braintrust.dev, Master Subscription Agreement: Master Subscription AgreementSource 4, trust.braintrust.dev, Security incident reports: Security incident reportsSource 9, braintrust.dev, Product updates (changelog): Product updates (changelog)Source 2, Braintrust, Plans and limits: Plans and limits

Details

Braintrust's MSA prohibits AI training on customer data. In May 2026, an attacker accessed decrypted provider keys in a migration backup. Hosted organizations now support workload identity federation for Anthropic and other providers, plus assume-role for Bedrock. SAML SSO and audit logs, along with a BAA and SOC 2 report, require Enterprise.

Signals

What is the current evidence saying about Braintrust?

Named teams at Dropbox, Fintool, Rox, Notion and Zapier gate releases on Braintrust experiments, and Parlance Labs found its Loop agent caught the most failures on 100 production traces. Builders report SDK problems, and some left for Langfuse or their own tools. Each finding links to its public sources.

Whose sources count

Practitioner sentiment, teams and leaders

+50 Strong positive net

of 34 sources that take a side, each author counted once.

How this figure is made

Current sentiment

Positive, mixed and negative sources

The score counts them as 19 positive, 10 mixed and 3 negative votes, one per author.

Team accounts lean positive: of the 34 team and leadership sources that give an opinion, 20 are positive, 11 mixed and 3 negative. Evaluation draws the most praise. Seven of 8 discussing trace-level debugging praise it. All 6 discussing SDK or ingestion reliability report problems. Teams also weigh building their own eval workflow. Platform decisions run 12 to 3 in favor of keeping or choosing Braintrust.

Run a pilot on one production app to measure which failures it surfaces and how long tracing them takes.

Evidence field. All 73 sources, one mark each.

Arrange by

Each mark is one source: positive, mixed, negative, no opinion stated, or documentation (not counted).

By sentiment, Teams and technical leaders. Every source GILD read, grouped as the field draws it.
GroupSourcesPositiveMixedNegativeNo opinion stated and not counted in the scoreDocumentation, checked and not counted
Positive20200000
Mixed11011000
Negative300300
Not counted700070
Documentation14000014
Outside this group1876410
Every source GILD read, by the quarter it was published, as the field's time axis counts it. Documentation is dated by the day it was checked.
QuarterSources
Q2 20257
Q3 20253
Q4 20256
Q1 202611
Q2 20267
Q3 202619
Q4 20266
Documentation, checked14

By sentiment

14 documentation pages check facts and are not counted; 18 sit outside this group.

Hover a mark for a quick look, click it or press Enter to open its source.Tap a mark to open its source, then step to its neighbors with Previous and Next.

What practitioners praise

Top praise of 3. Each mark is a source on it; filled marks praise it.

  1. Datasets, Experiments & Scorers20 of 21 sources on it praise it

Most common concerns

Top concern of 2. Each mark is a source on it; filled marks raise it.

  1. SDK & Ingestion ReliabilityAll 6 sources on it raise it as a concern
All 73 sources behind these findings
  1. Braintrust ruled out because self-hosting is Enterprise onlyCollectionPure7752, Reddit user, r/mlops (self-described: An early-stage team replacing Langfuse after letting non-engineers edit prompts), Reddit post, published Oct 22, 2026
  2. Living Evals: an eval suite that grows from productionBrian Xu, engineer on the Agents team at Rox (self-described: Rox's Agents team, with Devin writing evals from Braintrust production traces each week), Engineering blog post, Rox, published Oct 14, 2026
  3. Arize, Langfuse and Braintrust all intimidating at firstGanesh Iyer, AI payments builder and creator of the Nura family assistant (self-described: Tried the observability tools for his own agents), Post on X, published Oct 13, 2026
  4. Plans and limitsBraintrust (Official), Product documentation, checked Oct 12, 2026
  5. Billing FAQBraintrust (Official), Product documentation, checked Oct 12, 2026
  6. Monitor usageBraintrust (Official), Product documentation, checked Oct 12, 2026
  7. Configure data retentionBraintrust (Official), Product documentation, checked Oct 12, 2026
  8. Deployment optionsBraintrust (Official), Product documentation, checked Oct 12, 2026
  9. ArchitectureBraintrust (Official), Product documentation, checked Oct 12, 2026
  10. SecurityBraintrust (Official), Product documentation, checked Oct 12, 2026
  11. Protect sensitive dataBraintrust (Official), Product documentation, checked Oct 12, 2026
  12. ExperimentsBraintrust (Official), Product documentation, checked Oct 12, 2026
  13. Run experiments in CI/CDBraintrust (Official), Product documentation, checked Oct 12, 2026
  14. Score production tracesBraintrust (Official), Product documentation, checked Oct 12, 2026
  15. Trace LLM callsBraintrust (Official), Product documentation, checked Oct 12, 2026
  16. Send OpenTelemetry traces and logsBraintrust (Official), Product documentation, checked Oct 12, 2026
  17. Use the Braintrust GatewayBraintrust (Official), Product documentation, checked Oct 12, 2026
  18. feat(observability): Braintrust refuse-to-enable until compliance affirmed (audit C2/H7)mdenner1234, Developer (pull request author) (self-described: Tech Fleet network, member Q&A assistant), GitHub pull request, published Oct 10, 2026
  19. feat(evals): link Braintrust experiments to their CI run and the PRMatt Rossman (mattrossman), AI tooling at Supabase (self-described: Supabase evals repository, experiments run from GitHub Actions), GitHub pull request, published Oct 8, 2026
  20. Remove the Braintrust integrationdealvz, Developer (pull request author) (self-described: GoodParty.org omni platform: chat, briefings, PMF runner), GitHub pull request, published Oct 5, 2026
  21. Used Braintrust and did not enjoy it, built custom evals insteadOmrinachmani, Reddit user, r/LangChain (self-described: A developer running custom offline observability and evals after trying Braintrust), Reddit comment, published Sep 27, 2026
  22. Question: why does a self-hosted deploy's daemon contact www.braintrust.dev on cold start?LuizNascimentoTR, Developer (issue author) (self-described: Team running a self-hosted Braintrust deployment), GitHub issue, published Sep 25, 2026
  23. chore(eval-tests): upgrade eval deps, weekly evals, standalone Braintrust CLI CLOUDP-450203Nima Taheri (nima-taheri-mongodb), Contributor to MongoDB's MCP server (self-described: MongoDB MCP server, eval tests in CI), GitHub pull request, published Sep 25, 2026
  24. Remove Braintrust reporting and implicit judge gateway integrationaviggiano, Developer (issue author) (self-described: Ultrafuzz, Monad developers' fuzzing project), GitHub issue, published Sep 22, 2026
  25. Braintrust LLM observability: spans for every model call, off by defaultpunitarani, Developer (pull request author) (self-described: Personal research project calling models through OpenRouter), GitHub pull request, published Sep 21, 2026
  26. AI Evals: Everything You Need to KnowHamel Husain, AI evals consultant and course instructor (self-described: Advising client teams on eval tooling and vendor selection), Personal blog post, hamel.dev, published Sep 18, 2026
  27. feat: trace simulations to Braintrust instead of the GigaFlow SDKgiga-james, Developer (pull request author) (self-described: GigaFlow, tau2 agent simulations), GitHub pull request, published Sep 17, 2026
  28. feat(homelab): tail-sample LLM traces into Braintrust and repoint birmelshepherdjerred, Developer (pull request author) (self-described: Homelab services with an OpenTelemetry gateway), GitHub pull request, published Sep 10, 2026
  29. The same evals score production traffic, not only experimentsCheap-Ad-2360, Reddit user, r/LangChain (self-described: A team scoring production traffic with its release evals), Reddit comment, published Sep 9, 2026
  30. FunctionCall tool-span instrumentation for Agno leaks the full Agent/Team object (incl. model.api_key) into span metadatapaulosuzart, Developer (issue author) (self-described: Team tracing Agno agents with MCP tools), GitHub issue, published Sep 3, 2026
  31. Eval::Runner's per-case force_flush adds 10-25s+ per case even when no scorer/classifier uses trace:satanas, Developer (issue author) (self-described: Ruby eval suite), GitHub issue, published Aug 19, 2026
  32. Our PM runs prompt changes against the dataset without an engineerLow_Dust_9566, Reddit user, r/mlops (self-described: A team whose product manager changes prompts and reviews regressions), Reddit comment, published Aug 19, 2026
  33. Flue adapter: logging the full conversation-so-far per turn makes background-logger retention O(turns²), OOMs 128 MB Workers isolatesdknecht, Developer (issue author) (self-described: Production agent on Cloudflare Workers Durable Objects), GitHub issue, published Aug 11, 2026
  34. Migrate ThoughtForm observability to Langfuseadambelton, Developer (pull request author) (self-described: ThoughtForm, a personal app with five runtime prompts), GitHub pull request, published Aug 7, 2026
  35. The best evals we've written came from production failuresDisastrous_Injury561, Reddit user, r/mlops (self-described: A team that turns odd production traces into regression tests before each model upgrade), Reddit post, published Aug 5, 2026
  36. Back model benchmark with Braintrust, drop in-house scoringtime-attack, Developer (pull request author) (self-described: GStack model benchmark driving Claude, Codex, and Gemini CLI agents), GitHub pull request, published Jul 21, 2026
  37. feat(evals): bump braintrust to 3.x; first-party BraintrustSpanProcessor OTEL sinkMiguel (miguelg719), Contributor to Browserbase's Stagehand evals (self-described: Browserbase Stagehand, browser-agent evals), GitHub pull request, published Jul 13, 2026
  38. Auto-evals: Braintrust Loop, Arize Alyx and LangSmith on the same 100 tracesAntaripa Saha and Hamel Husain, Parlance Labs (self-described: 100 hand-labelled traces from a production apartment-leasing assistant), Independent evaluation, Parlance Labs blog, published Jul 11, 2026
  39. Retire Braintrust for Langfusecreatesomethingtoday, Developer (pull request author) (self-described: Create Something monorepo: evals, telemetry, prompts, and MCP services), GitHub pull request, published Jul 6, 2026
  40. How Braintrust uses AI agents, evals, and CI to ship better softwareAnkur Goyal, founder and CEO of Braintrust, on How I AI with Claire Vo (self-described: Braintrust's own engineering team, using coding agents, evals and CI), Podcast episode, How I AI, published Jun 15, 2026
  41. feat(photo-curation): local eval store + runner (replace Braintrust write path)julianken, Developer (issue author) (self-described: Photo-judge eval for a personal bird-sighting system), GitHub issue, published Jun 12, 2026
  42. Standalone-api / brainstore v2.1.1 ships starlette < 1.0.1 (CVE-2026-48710)joel-vaz, Developer (issue author) (self-described: Self-hosted data plane on the Helm chart), GitHub issue, published May 28, 2026
  43. Combine Skills and MCP to Close the Context GapPedro Rodrigues, AI tooling engineer, Supabase (Supabase testing coding agents with its MCP server and Agent Skills), Conference talk with transcript, AI Engineer Europe 2026, published May 15, 2026
  44. Shipping complex AI applications: Braintrust & TrainlineOussama Hafferssas and Mayank Soni, Engineers at Trainline (self-described: Trainline travel assistant: refunds, train changes, and handover to support), Conference talk (co-presented with Braintrust), AI Engineer Europe 2026 (YouTube), published May 1, 2026
  45. Replacing 12K LoC with a 200 LoC SkillDavid Gomes, Engineer on coding agents, Cursor (Cursor team replacing its worktree feature with an agent skill), Conference talk with transcript, AI Engineer Europe 2026, published Apr 30, 2026
  46. feat(observability): replace Arize with Braintrust OTel + exact wire logging via Finch telemetryBlueHotDog, Developer (issue author) (self-described: Frontman, agent platform on Elixir), GitHub issue, published Apr 10, 2026
  47. setup_adk() does not trace tool calls in nested sub-agentssm-stripe, Developer (issue author) (self-described: Google ADK pipeline with nested sub-agents), GitHub issue, published Mar 24, 2026
  48. Comment on: Ask HN: How are people doing AI evals these days?mierz00, Hacker News commenter (self-described: Team using an LLM for classification), Hacker News comment, published Mar 17, 2026
  49. Comment on: Ask HN: How are people doing AI evals these days?mierz00, Hacker News commenter (self-described: Team using an LLM for classification), Hacker News comment, published Mar 11, 2026
  50. Regular 500 responses from /logs3CodingCanuck, Developer (issue author) (self-described: Team eval pipeline on the TypeScript SDK), GitHub issue, published Feb 27, 2026
  51. Significant latency regression between TypeScript SDKs v0.4.10 and v1.0.0CodingCanuck, Developer (issue author) (self-described: Team eval pipeline on the TypeScript SDK), GitHub issue, published Feb 19, 2026
  52. chore(sc-41159): Add Braintrust evaluation cronjob infrastructureyodem, Developer (pull request author) (self-described: Sefaria, AI chatbot in production), GitHub pull request, published Feb 4, 2026
  53. Lessons from Building AI Agents for Financial ServicesNicolas Bustamante, Founder of Fintool (Fintool, AI agents for financial research and equity analysis), Personal blog post, nicolasbustamante.com, published Jan 24, 2026
  54. Remote Evals (examples and support)gabe-kent, Developer at a Braintrust customer (issue author) (self-described: Customer organization with a main Rails app), GitHub issue, published Jan 13, 2026
  55. Comment on: Ask HN: Where are you keeping your LLM logs?barbazoo, Hacker News commenter (self-described: Hacker News thread: Where are you keeping your LLM logs?), Hacker News comment, published Jan 9, 2026
  56. feat: implement remote Braintrust evals for all HolmesGPT testsaantn, Maintainer (pull request author) (self-described: HolmesGPT, an open-source SRE agent, with about 53 LLM evals), GitHub pull request, published Jan 3, 2026
  57. LangFuse Telemetry not working, switch to Braintrustfyang0507, Developer (issue author) (self-described: Personal Notion agent, CLI and Next.js app), GitHub issue, published Jan 1, 2026
  58. Migrate to Braintrust-native eval frameworkNick Sullivan (TechNickAI), Builder at Carmenta Collective (self-described: Carmenta, evals for model routing and file handling), GitHub pull request, published Dec 11, 2025
  59. Ask HN: What do u use for agent/agentic evals?hhthrowaway1230, Hacker News commenter (self-described: Evaluating agents), Hacker News post, published Nov 25, 2025
  60. Node.js SDK has broken/bad bundlingai-simple-ai, Developer (issue author) (self-described: Team patching the SDK locally), GitHub issue, published Nov 20, 2025
  61. BOLT - How Mura wrote an in-house LLM Eval FrameworkJames Mackey, Co-founder of Mura (self-described: Mura, seed-stage startup automating billing for commercial HVAC providers), Engineering blog post, James's Newsletter (Substack), published Oct 21, 2025
  62. A practical blueprint for evaluating conversational AI at scaleRanjitha Gurunath Kulkarni, Ameya Bhatawdekar, and Gonzalo Garcia, Dropbox Dash engineers (Dropbox Dash, a conversational AI search product), Engineering blog post, Dropbox Tech blog, published Oct 2, 2025
  63. Selecting The Right AI Evals ToolHamel Husain, AI evals consultant and course instructor (self-described: Three-person panel that watched LangSmith, Braintrust, and Arize Phoenix complete the same eval assignment), Independent evaluation, hamel.dev, published Oct 1, 2025
  64. Evals your LLM driven Agents (Experiments and Lessons Learned) with BraintrustAIForOver50Plus, Reddit user, r/LLMDevs (self-described: Weekend experiments with an email management agent), Reddit post, published Sep 28, 2025
  65. If you log a span instance, your API key is included in the logAustin Tackaberry (austintackaberry), Co-founder and CTO at Levenza (self-described: Levenza, logging with the Braintrust TypeScript SDK), GitHub issue, published Sep 7, 2025
  66. Evals Are Not Unit TestsIdo Pesok, engineer on v0, Vercel (Vercel v0 team running evals in CI and on a daily schedule), Conference talk with transcript, AI Engineer World's Fair 2025, published Aug 6, 2025
  67. Turning Fails into Features: Zapier's Hard-Won Eval LessonsRafal Wilinski, Tech Lead for Zapier Agents, with Vitor Balocco (Zapier Agents team comparing models on Braintrust experiments), Conference talk with transcript, AI Engineer World's Fair 2025, published Jun 30, 2025
  68. How to build world-class AI products: Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)Sarah Sachs, Engineering lead, AI modeling, at Notion (self-described: Notion AI team: engineers, data specialists, PMs and designers), Conference talk (co-presented with Braintrust), AI Engineer World's Fair 2025 (YouTube), published Jun 27, 2025
  69. The Web Browser Is All You NeedPaul Klein IV, Founder and CEO, Browserbase (Browserbase, browser infrastructure for AI agents), Conference talk with transcript, AI Engineer World's Fair 2025, published Jun 20, 2025
  70. Ask HN: What tools are you using for AI evals? Everything feels half-bakedfazlerocks, Hacker News commenter (self-described: Team running LLMs in production for content generation, customer support, and code review assistance), Hacker News post, published Jun 5, 2025
  71. test(max): Migrate insight deepevals to BraintrustMichael Matloka (Twixes), Engineer at PostHog (self-described: PostHog Max AI, evals for generated insight queries), GitHub pull request, published May 6, 2025
  72. Review of BraintrustHowie Liu, Product Hunt reviewer, Airtable (self-described: Airtable AI Assistant), Product Hunt review, published Apr 9, 2025
  73. Unit-testing AI agents in the browserAnirudh Kamath and Sean McGuire, Browserbase Stagehand team (self-described: Stagehand browser-agent SDK, model comparison on its eval suite), Engineering blog post, Browserbase blog, published Apr 9, 2025

Apr 2025 to Oct 2026.

59 sources from practitioners, by month and sentiment.

The full readExplore all Braintrust Signals3 praise themes, 4 concerns, 3 points of agreement and 1 disagreement across all three groups, with all 73 sources open to inspect.

Where It Fits

Where does Braintrust belong in the stack?

Open Where It Fits: the Stack Field and the full map

Braintrust is Core across Evaluate and Operate, supports Model and Build, and touches Data.

Business area
Product & Engineering
Function
Software Development
Operating stack
AI Application Platform
Primary role
AI Evaluation & Observability
Braintrust beside the rest of its stackThe Stack Field, every product on every layer
FootprintBraintrust across the AI Application Platform stack. Bar height is its role on each layer.

  1. Model

    1. Model APIs: Touches

      Model APIs, touches. Braintrust's built-in models serve playgrounds and scorers, plus Topics and Loop, using monthly model credits. Applications access production models through OpenAI, Anthropic, Google, and the other providers Braintrust records.

    2. Model gateway: Supports

      Model gateway, supports. Braintrust Gateway exposes providers through one OpenAI-compatible API with caching and logging. Self-hosted data planes can run it. The hosted Gateway has no SLA and is not generally available, so production routing remains with a dedicated gateway.

  2. Build

    1. Orchestration: Touches

      Orchestration, touches. Braintrust traces agents built with LangGraph, the Vercel AI SDK, the OpenAI Agents SDK, the Claude Agent SDK, CrewAI, and other frameworks. It has no agent framework of its own.

    2. Tool use: Supports

      Tool use, supports. Braintrust records tool calls and hosts tool and scorer functions that models invoke. Coding agents query logs and experiments through its MCP server. The application's framework owns tool execution.

  3. Data

    1. Retrieval: Touches

      Retrieval, touches. Braintrust traces and scores retrieval, including whether an answer uses the retrieved context. The application embeds and indexes its documents and stores them elsewhere.

  4. Evaluate

    1. Evaluation: Core

      Evaluation, core. Braintrust tests changes through datasets and experiments in code, the UI, or CI. Teams compare runs side by side using code and LLM scorers, plus human review and playgrounds.

  5. Operate

    1. Observability: Core

      Observability, core. SDKs in six languages and OpenTelemetry send traces to Brainstore. Teams search logs and score production traffic there. Topics groups the logs, and SQL thresholds trigger alerts.

    2. Cloud deployment: Touches

      Cloud deployment, touches. Braintrust versions and serves prompts and runs its own functions. Enterprise data planes can run in your cloud. Braintrust supplies no application hosting or model capacity.

    3. Guardrails: Touches

      Guardrails, touches. Braintrust online scoring runs scorers automatically on production logs for quality and safety analysis. It evaluates recorded conversations and does not sit in the request path to block them.

Market mapThe layers Braintrust covers, and who else owns each one.

  1. Evaluation & testing

    CoreEvaluate

  2. Observability & tracing

    CoreOperate

  3. Model gateways & routing

    SupportsModel

  4. Tool use & integrations

    SupportsBuild

  5. Model APIs

    TouchesModel

4 more layers on the full map. Core, Supports and Touches describe coverage. They say nothing about quality.

Models

Which models run in Braintrust?

The current releases GILD tracks that public sources record running in Braintrust. Each model's page charts its public benchmark scores.

  1. GPT-6 LunaOpenAI's most efficient GPT-6 model, for focused, high-volume tasks. API model gpt-6-luna, with a 1,050,000-token context on the OpenAI API; Microsoft Foundry caps input at 922,000 tokens.GPT LunaBenchmarks

More on Braintrust

  1. GILD ReviewGILD's evaluation, with the buying facts
  2. Research2 pieces
  3. Guides3 guides
  4. Operator Insights12 operator accounts
  5. Where It FitsOn the AI Application Platform stack
  6. Related Products6 products