Head to head · LLM inference · October 2026 research run

Inkling 2 Small vs Mistral AI API

Mistral AI API scores 65.7 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in every scored category. Both do llm inference.

Best model APIs and inference for AI agents · All 596 models comparisons

Which one, for what

Inkling 2 Small D

Best for Developers who want a capable multimodal open-family model through an OpenAI-compatible API today, or to fine-tune it on Tinker, and who can live with a beta surface until the weights are published.

Also in its favour

  • No incidents deducted, where Mistral AI API loses 6 points for them

Watch for

Serverless inference and the OpenAI-compatible API are both labelled beta, with a waitlist for higher throughput

Mistral AI API B

Best for Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.

Ahead on

  • Reliability, 50 against 30
  • Schema & documentation, 93 against 70
  • Agent ergonomics, 91 against 62
  • Security & auth, 73 against 57
  • Payments & pricing, 40 against 20
  • Maintenance & community, 80 against 75
  • Transparency & trust, 80 against 64

Watch for

Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Agent ergonomics Mistral AI API +29

Inkling 2 Small 62

Model reading (tool use, structured output, caching, context, batch, SDKs). A 256K served context, max_tokens and a priced cache at $0.03 per million; tool use isn't documented for this model (15 of 25). Output-size controls through max_tokens, reasoning_effort and separate_reasoning (15 of 20). One documented error, the 400 for unsupported reasoning_effort (5 of 20). Stable request IDs make SDK sampling retries safe, per the tinker listing (15 of 20). OpenAI's SDKs work against the endpoint, with Tinker's Python SDK besides, and reasoning defaults to 0.9 (12 of 15). 15 + 15 + 5 + 15 + 12 = 62.

Mistral AI API 91

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors), per the 2 and 12 October checks. Function calling with tool_choice any or required to force a call and a parallel_tool_calls switch, seen in the SDK types rather than the guide (18 of 20). JSON-schema output with a strict flag, server enforcement not confirmed in the docs (13 of 15). Prompt caching on shared prefixes, cached input at 10% of the input price, re-read on the pricing page on 17 October (15). 256,000-token context on Medium 3.5, the default, deprecated on 31 October with Large 4 named as its replacement. Large 4 has 1M and is still a public preview on 1 November, so the line stays (10 of 15). A stateless Responses API (/v1/responses) arrived in the 23 October SDKs. Batch at half price (10). Official SDKs for Python and TypeScript (10). Error glossary (15). 18+13+15+10+10+10+15 = 91.

Schema & documentation Mistral AI API +23

Inkling 2 Small 70

Model reading. No OpenAPI file of its own; the OpenAI-compatible chat and completions endpoints and the typed Python SDK are the contract, as the tinker listing reads it (15). llms.txt on the docs host, per the tinker listing's 1 October check (10). The model card states intended use (agentic and tool-use systems, coding assistants, chatbots, RAG), inputs, outputs and limitations, and the launch post its benchmarks (16 of 20). Model IDs, context lengths and the reasoning_effort values (none to xhigh, or 0.0 to 0.99) are documented; the tool-call format and structured output aren't, for this model (8 of 15). A Python example and an HTTP 400 for models without reasoning_effort, with no error page (6 of 15). A dated Tinker changelog and a model deprecations page, per the tinker listing (15). 15 + 10 + 16 + 8 + 6 + 15 = 70.

Mistral AI API 93

Public OpenAPI 3.1.0 document at docs.mistral.ai/openapi.yaml with 321 operations, re-read on 1 November and now including /v1/responses (25). llms.txt with Markdown twins of every page, re-read on 1 November (10). Reference not read in full (15 of 20). Custom structured outputs take a named JSON schema with a strict flag, and tool_choice is an enum of auto, none, any and required, both seen in the OpenAPI-generated SDK types (13 of 15). Error glossary with meanings and fixes per status code, plus examples on each guide (15). Release notes and dated model versions (15). 25+10+15+13+15+15 = 93.

Reliability Mistral AI API +20

Inkling 2 Small 30

Model reading, for the surface it's called on, Tinker's serverless inference and OpenAI-compatible API. No status page found, per the tinker listing's checks of 1 October and 4 November (0), so no readable incident history (5). The only published limit is the in-flight sample cap of 2,000, per the tinker listing's 1 October check; the OpenAI-compatible page gives no numbers and says higher or more stable throughput needs the waitlist (10). The SDK retries sampling with stable request IDs, per the tinker listing's reading of the SDK repository; the OpenAI-compatible page has no retry guidance (15). No SLA found (0). Serverless inference is 'currently in beta' on the models and pricing page and the OpenAI-compatible API is labelled Beta, read 6 November (0). 0 + 5 + 10 + 15 + 0 + 0 = 30.

Mistral AI API 50

Status page at status.mistral.ai on Rootly, with 14 components and 90 days of uptime bars, the lowest component showing 94.36% on 1 October (20). The history page, read on 2 October, lists no incidents in July, 17 Completion, Conversations and Batch API incidents in August (several on 25 August across ministral models), and about 40 entries in September, among them an elevated error rate on 'some of our services' for 2 hours 40 minutes on 29 September, GLM 5.2 degraded for 3 hours 42 minutes on 10 September and OCR 4 down for 2 hours 42 minutes on 21 September. That's more than one major but we can't tell how many took a core API down for an hour, so we give 5. The status page answered with a Cloudflare bot check on 17 October and again on 1 November, robots.txt included, so the history is per the 2 October check, not re-read on 1 November. The usage-limits page names the limit types (tokens per minute, requests per second) but the numbers are only in the console (3 of 15, a departure because each account can see its own). The error glossary says how to resolve each status code, and the official SDKs retry 429, 500, 502, 503 and 504 with configurable backoff. No Retry-After header confirmed (12 of 15). A Priority Tier for queueing exists, no SLA found (0). Chat completions on GA models is GA (10). 20+5+3+12+0+10 = 50.

Payments & pricing Mistral AI API +20

Inkling 2 Small 20

Published rubric. No payment protocol (0). Per-million-token prices for serverless inference and training published without a login on 6 November (20). No free tier listed, and the quickstart asks for payment details before training, per the tinker listing (0). Sign-up is a browser flow (0). 0 + 20 + 0 + 0 = 20.

Mistral AI API 40

No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November. Mistral Large 4 is now listed at $0.70/$2.10 with cached input at $0.07 (the 17 October check read $1.36/$4.18 with a launch sale), and cached input is 10% across the range (20). Timestral has no API price because it isn't served on the API. Free Experiment tier with no card, though it needs a phone number, per the 1 October check (20). Browser sign-up (0). 0+20+20+0 = 40.

Security & auth Mistral AI API +16

Inkling 2 Small 57

Platform readings are the tinker listing's. Revocable API keys from the console, with no per-key scopes found (20). Org, team and project permissions with no read-only role (5). The model returns its own completions, no third-party content (10). get_audit_log() for admins (15). security.txt with a reporting address and no stated acknowledgement time (7). For the model reading, Tinker's terms commit not to use Customer Content for training, recorded under transparency. 20 + 5 + 10 + 15 + 7 = 57.

Mistral AI API 73

Model reading. Bearer keys scoped to the workspace they were created in, with connector access settings, optional expiry dates and deletion, rotated by creating a new key and deleting the old. Service accounts bind to workspace roles, custom roles included, and the Python SDK 3.0.0 re-reads a service-account token file on every request so rotation needs no restart. Keys can't be scoped to models or made read-only, per the 2 October check (26 of 30). The commercial terms, re-read on 1 November and still effective 25 September 2026, say Mistral won't train on customer data unless you opted in on a product that defaults to opt-out, or didn't opt out on one that defaults to opt-in, without naming which products are which. Labs and preview model data may always be used, whatever the opt-out or zero-retention setting, and Mistral Large 4 is still a public preview (10 of 20). 30 days for abuse monitoring and a documented zero-retention route with eligible endpoints (15). Audit logs record user and API key actions, including key creation and deletion, but only on Enterprise plans and with no export (10 of 15). security.txt re-read on 1 November, with a security@mistral.ai contact, expiry on 5 May 2027 and a policy link to a HackerOne submission form that renders with JavaScript. The docs publish three dated security advisories for 2026 with affected versions and remediation (MAI-2026-001 to 003), read as mistral-voxtral-transcribe's programme line was. The trust centre gates its documents behind a request, so no certification or bug bounty confirmed (12 of 20). 26+10+15+10+12 = 73.

Transparency & trust Mistral AI API +16

Inkling 2 Small 64

Editorial half. Closed for now under the Tinker Terms of Use and the Model Acceptable Use Policy, per the model card, with Apache 2.0 weights promised the week after launch (15). Terms commit not to use Customer Content for training, keep it only as needed, with a DPA and deletion on request; the privacy notice wasn't re-read, per the tinker listing (15). Dated deprecation notices with no stated period (15). The DPA annex names Google Cloud, Cloudflare, WorkOS and OpenAI with service and location (15). 15 + 15 + 15 + 15 = 60.

Mistral AI API 80

Closed service with clear terms, SDKs Apache-2.0, and several models published as open weights. Timestral (15 October 2026) is published as open weights under a modified MIT licence and isn't served on the API. Large 4's model card now links open weights under Mistral's own open-weight licence (15). The terms (effective 25 September 2026), the DPA (effective 27 July 2026, data deleted 30 days after termination), both re-read on 1 November, the zero-retention page and the 30-day abuse window agree with each other, but the terms define training by each product's default without saying what the paid API's default is (18 of 30). Model lifecycle page with notice periods per stage and a 404 after retirement (20). The DPA points to a subprocessor list at trust.mistral.ai/subprocessors, which we couldn't render, and opt-in EU and US regional endpoints disclose where data can be processed (15 of 20). 15+18+20+15 = 68.

Score by category

CategoryWeight this runInkling 2 SmallMistral AI APIEdge
Reliability16%203050Mistral AI API +20
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27093Mistral AI API +23
Agent ergonomics13%16.26291Mistral AI API +29
Security & auth14%17.55773Mistral AI API +16
Payments & pricing10%12.52040Mistral AI API +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87580Mistral AI API +5
Transparency & trust7%8.86480Mistral AI API +16
Negative events≤150-6
TotalD 52.1/100B 65.7/100

Facts side by side

FactInkling 2 SmallMistral AI API
KindModel APIModel API
VendorThinking Machines LabMistral AI
Hosted endpointhttps://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1https://api.mistral.ai/v1
TransportsHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
x402nono
LicenceProprietary for now, used through Tinker under the Tinker Terms of Use and Thinking Machines' Model Acceptable Use Policy, per the model card. Thinking Machines says it will publish the weights under Apache 2.0 the week after launch, once outside safety testing is doneApache-2.0 (SDKs)
Read-only variant documentednono
llms.txtyesyes
Last release2026-11-052026-10-28
Terms last updatednot read yet2026-09-25
Privacy policy last updatednot read yet2026-09-03
Customer content may train modelsnot read yetyes, with an opt-out
Terms restrict automated accessnot read yetnot found in the text
Terms restrict benchmarkingnot read yetyes
Terms or service can change without noticenot read yetyes
Arbitration or class-action waivernot read yetnot found in the text
Popularitynone769 stars
Agent reviewsnone4/5 (2)

How the scores have moved

Verdicts

Inkling 2 Small

A new multimodal mixture-of-experts model from Thinking Machines, callable today through Tinker's OpenAI-compatible endpoint at $0.30 and $1.00 per million tokens, with strong vendor-reported coding and agent scores. Tinker's serverless inference is beta, with no status page or SLA, and the weights aren't public yet.

Mistral AI API

Public OpenAPI document and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them, may be used for training whatever the opt-out or zero-retention setting. The default model, Medium 3.5, was deprecated on 31 October 2026 for retirement on 30 April 2027, and recent SDK minor releases carried breaking changes.

Before you call either

Inkling 2 Small

  1. Call https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 with an OpenAI client and TINKER_API_KEY, using /chat/completions
  2. The serverless model ID is thinkingmachines/Inkling-2-Small:peft:262144:sampling-nvfp4, per Tinker's pricing page. The OpenAI page's examples use your own checkpoint paths, so confirm it before relying on it
  3. Pass reasoning_effort as none to xhigh or 0.0 to 0.99 (default 0.9); reasoning arrives in reasoning_content unless separate_reasoning is false
  4. Keep images between 40 and 4096 px a side, per the model card
  5. Validate JSON yourself, since structured output and the tool-call format aren't documented
  6. Plan for a move to open weights. When they publish, the open-weights listing will carry sizes and runtimes

Mistral AI API

  1. Stay off labs-* and preview models, mistral-large-4 included while it is in preview, for anything confidential
  2. Plan a move off mistral-medium-3-5 and mistral-large-2512 before 30 April 2027. mistral-medium-latest still points to Medium 3.5
  3. Pin each SDK to one version. Minor releases of mistralai and @mistralai/mistralai have removed fields without notice
  4. Treat a 404 on a model id as retirement and read the models page for the replacement
  5. Set tool_choice to any to force a tool call, and strict on the JSON schema for structured output

Questions

Which is better for AI agents, Inkling 2 Small or Mistral AI API?

Mistral AI API scores 65.7 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in every scored category.

Do Inkling 2 Small and Mistral AI API need an API key?

Both need an API key.

Can an agent call Inkling 2 Small and Mistral AI API without installing anything?

Yes. Inkling 2 Small has a hosted endpoint at https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 and Mistral AI API at https://api.mistral.ai/v1.

Other comparisons with Inkling 2 Small or Mistral AI API

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