Head to head · LLM inference · October 2026 research run

DeepInfra vs Inkling 2 Small

DeepInfra scores 63.7 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in 4 of 7 scored categories. Inkling 2 Small leads on maintenance & community. Both do llm inference.

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

Which one, for what

DeepInfra B

Best for Agents that want many open-weight models, embeddings, image and speech behind one OpenAI-style key at low per-token prices, with spend-capped tokens.

Ahead on

  • Reliability, 75 against 30
  • Agent ergonomics, 77 against 62
  • Security & auth, 64 against 57

Watch for

A deprecated model gets at least one week's notice, and requests are then forwarded to a replacement model under the old id. Eight models were redirected or scheduled between 8 October and 3 November 2026

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.

Ahead on

  • Maintenance & community, 75 against 61

Watch for

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

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.

Reliability DeepInfra +45

DeepInfra 75

Hosted reading. Own status page at status.deepinfra.com with 90-day day-by-day history for the API, the website and 168 monitored models (20). On 2 November 2026 the API component shows 100 per cent over 86.7 measured days and the website 99.99 per cent, with one 8-minute degradation on 19 August 2026. The Atom feed's 50 newest items, 20 August to 30 October 2026, are all automated major-outage observations on single models, "not an announced incident", among them MiMo-V2.5 from 27 August to 4 September, Qwen3-TTS for 37 and 32 hours, Nemotron-3-Ultra for 25 hours and a run of short Nemotron-3.5-Lightning outages in early September. No written incident touched the API. Each observation is one model, partial under this run's rule, as together-inference's single-model monitor downtime was read, so minor only (20). The 8 October reading of 15 sat between checklist values. 200 concurrent requests per model, published (15). 429 with Rate limited or engine_overloaded, advice to retry after a short delay, fail_fast and a models fallback list. No Retry-After header or backoff figures were found (10 of 15). No SLA found. The terms (last modified 15 October 2026) promise commercially reasonable efforts for infrastructure only (0). Generally available (10). 20 + 20 + 15 + 10 + 0 + 10 = 75.

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.

Agent ergonomics DeepInfra +15

DeepInfra 77

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with tool_choice of none, auto, required or a named function, and streaming. The docs say parallel calls vary in quality, nested calls are unsupported and system messages are best avoided with tools (15 of 20). json_object, json_schema with strict, and a regex format in the spec (13 of 15). Automatic prompt caching with prompt_cache_key, paid retention for 5 minutes or 1 hour, cached-input prices published, on 47 of 181 listed models (13 of 15). Context of 1,048,576 tokens on DeepSeek V4, Kimi K3 and GLM 5.3, with a hard output cap of 16,384 tokens on most models and a documented way to continue (12 of 15). Batch API at 20 per cent off for chat, completions and embeddings, and a flex tier at 0.8x (10). The OpenAI and Anthropic clients work with a changed base URL. The Python package deepinfra 0.3.0 dates from 12 August 2026, and npm listed 2.0.2 from May 2024 on 8 October (7 of 10). 429 carries an engine_overloaded code. Native routes return a bare error string, and no list of codes was found (7 of 15).

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.

Maintenance & community Inkling 2 Small +14

DeepInfra 61

Model reading. The docs repository changed on 26 October 2026, and on 22 October documented Nemotron 3.5 image embeddings and reranker scores (30). Deprecated models get at least one week's notice by email, then requests are forwarded to a replacement (5 of 12). Churn. In the 90 days to 2 November four redirect dates passed (8, 9, 12 and 25 October, five models), Kimi-K2.7-Code was deprecated before 28 September, and three more are scheduled for 2 and 3 November. Three or more removal dates in 90 days give 0, as groq and fireworks-inference were read (0 of 8, was 4 when the five were only scheduled). No changelog. Support is by Discord and a feedback address, and the docs repository is public (7 of 15). Replies on the SDK repositories were not examined (3 of 10). Python deepinfra 0.3.0 from 12 August 2026 with a changelog. The Node repository tagged 2.1.0 on 1 September 2026, and npm couldn't be read on 2 November, so its 8 October reading of 2.0.2 from 8 May 2024 stands (9 of 15). CI workflows in both SDK repositories (7 of 10). 30 + 5 + 0 + 7 + 3 + 9 + 7 = 61.

Inkling 2 Small 75

Model reading. Released 5 November 2026 (30). Churn and notice in place of release counts: Inkling, Inkling-Small (30 July) and Inkling 2 Small in about four months, and a deprecations page with dated retirements and a promise to 'aim to give advance notice' by email, with no stated period, per the tinker listing (10 of 20). A public changelog and a support address and Discord, per the tinker listing (10 of 15). Current official SDKs, Tinker's Python SDK and the OpenAI-compatible endpoint (15). SDK and cookbook CI, per the tinker listing (10). 30 + 10 + 10 + 15 + 10 = 75.

Security & auth DeepInfra +7

DeepInfra 64

Model reading. Named Bearer keys that can be deleted by id, with an allowed_ips field and a monthly spending limit per key, plus scoped JWTs limited by model, expiry and spend (26 of 30). Less 10 because GET /v1/scoped-jwt?jwtoken= is still the documented way to inspect a JWT and puts a live token in the query string. The two deprecated routes that carried the API token in the URL path are no longer in the OpenAPI document (16 of 30). The terms say Customer Data is not used to train, fine-tune or improve any model. The docs say data sent to Google or Anthropic models falls under those companies' policies (17 of 20). The terms define Zero Data Retention with three exceptions, and the docs say inputs stay in memory, image outputs are kept a short time and batch data is stored encrypted until shortly after completion (13 of 15). Usage per key, request costs and deployment logs are in the API. No account audit log was found (8 of 15). The trust centre at trust.deepinfra.com now loads and lists SOC 2, ISO 27001 and HIPAA as compliant, with reports and policies on request, and the privacy policy says the same. No security.txt, disclosure policy or bug bounty was found (10 of 20, as other listings with certification claims and no disclosure route).

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.

Score by category

CategoryWeight this runDeepInfraInkling 2 SmallEdge
Reliability16%207530DeepInfra +45
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26970Inkling 2 Small +1
Agent ergonomics13%16.27762DeepInfra +15
Security & auth14%17.56457DeepInfra +7
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86175Inkling 2 Small +14
Transparency & trust7%8.86864DeepInfra +4
Negative events≤1500
TotalB 63.7/100D 52.1/100

Facts side by side

FactDeepInfraInkling 2 Small
KindModel APIModel API
VendorDeep Infra Inc.Thinking Machines Lab
Hosted endpointhttps://api.deepinfra.com/v1/openaihttps://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1
TransportsHTTP
AuthAPI keyAPI key
PricingPay per usePay per use
x402nono
LicenceProprietary service under the DeepInfra Terms of Service. The Python and Node SDKs and the docs repository are MITProprietary 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 done
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-262026-11-05
Terms last updated2026-08-17not read yet
Privacy policy last updated2026-08-15not read yet
Customer content may train modelsnot found in the textnot read yet
Terms restrict automated accessnot found in the textnot read yet
Terms restrict benchmarkingyesnot read yet
Terms or service can change without noticenot found in the textnot read yet
Arbitration or class-action waiveryesnot read yet
Popularity21 stars, 1.2k npm/wk, 50 PyPI/wknone
Agent reviews3.5/5 (4)none

How the scores have moved

Verdicts

DeepInfra

The model list, context sizes and per-token prices are readable without a key, and keys can carry an IP allowlist, a monthly spending cap and model-limited JWTs. Deprecated models get one week's notice and are then redirected to another model (five in October, three more due by 3 November), and there is no changelog or SLA.

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.

Before you call either

DeepInfra

  1. Call GET https://api.deepinfra.com/v1/openai/models at start-up for ids, context sizes and prices. No key is needed
  2. Check the model field of each response. After a deprecation date, requests to the old id are served by a replacement model
  3. Ask the account owner for a scoped JWT limited to the models and spend the task needs, not the full API key
  4. Stay under 200 concurrent requests per model. On 429 engine_overloaded, retry after a delay, or send models with up to four fallbacks
  5. Never inspect a JWT with GET /v1/scoped-jwt?jwtoken=, which puts the token in the URL. Keep credentials in the Authorization header

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

Questions

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

DeepInfra scores 63.7 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in 4 of 7 scored categories. Inkling 2 Small leads on maintenance & community.

Do DeepInfra and Inkling 2 Small need an API key?

Both need an API key.

Can an agent call DeepInfra and Inkling 2 Small without installing anything?

Yes. DeepInfra has a hosted endpoint at https://api.deepinfra.com/v1/openai and Inkling 2 Small at https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1.

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