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AI Model Feature Support Matrix

A caniuse-style table of which production LLM APIs support each developer feature — vision, function calling, JSON mode, prompt caching, batch, PDF input, reasoning and more. Pick a feature to see every model that has it, or a model to see everything it can do. Cited to provider docs, no signup.

By Induwara AshinsanaUpdated Jul 17, 2026
Filter the matrix

28 of 28 models

supported~partial / betanot supported — tap a model name for its full capability list.

Feature support matrix: models down the left, developer features across the top. Check means supported, tilde means partial or beta, dash means not supported.
ModelVisionToolsJSON outCachingBatchFine-tuneAudio inAudio outPDF inVideo inStreamReasoningWeb searchCode exec
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Tap any model name in the matrix to see its full capability list, context window, and the provider doc the values came from.

Compare two models

3 of 14 features differ. Differences are highlighted.

  • Vision (image input) Supported Supported
  • Tools / function calling Supported Supported
  • Structured output / JSON mode Supported~ Partial / beta
  • Prompt caching Supported Supported
  • Batch API Supported Supported
  • Fine-tuning~ Partial / beta Not supported
  • Audio input Not supported Not supported
  • Audio output Not supported Not supported
  • PDF / document input Supported Supported
  • Video input Not supported Not supported
  • Streaming Supported Supported
  • Reasoning / extended thinking Supported Supported
  • Built-in web search~ Partial / beta Supported
  • Code execution~ Partial / beta~ Partial / beta

Every cell is compiled from the provider's official API docs and carries a source link in the detail panel. This is a static table — no request is sent to any provider. Sources and the last-verified date are listed below the tool. Spotted a stale value? Email me and I'll fix it.

How it works

This is not a calculator — it is a capability lookup, so correctness means one thing: fidelity to the official provider documentation. The matrix covers 28 current models across seven providers (OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek and xAI) and 14 developer features — 392 cells in total, each set by hand from a provider doc rather than guessed or scraped.

Every cell resolves to one of three states:

  • Supported— the feature is generally available on that model's hosted API.
  • ~ Partial — real but caveated: in beta or preview, delivered through a separate tool or endpoint, or model-specific. Every partial cell carries a note in the detail panel explaining exactly why.
  • Not supported— the provider docs do not offer it on that model's API.

The filtering is a set of pure, deterministic functions. Selecting feature chips runs matchesFeatures(model, selected, mode): in Match ALL mode a model qualifies only when every selected feature is supported or partial; in Match ANY mode it qualifies when at least one is. Provider and model-name filters compose on top with plain set membership and a case-insensitive substring match. An empty selection is a no-op, so the matrix always shows the full catalogue by default rather than a dead, empty page.

For credibility the module also exposes a compareModels(a, b) cross-check: it reads the exact same feature records the matrix renders and returns a feature-by-feature diff, so a single cell and the compare panel can never disagree. A matrixCoverage() self-test confirms all 392 cells resolve to a concrete value — no silent gaps. Because everything is static, there are no live API calls; the table is versioned with a LAST_VERIFIED date (2026-07-17) and every model row links to the provider doc it was read from.

Worked examples

Document-Q&A build: PDF input + caching + batch

  1. Filter chips: PDF input, Prompt caching, Batch API — Match ALL.
  2. matchesFeatures keeps a model only if all three are ✓ or ~.
  3. 15 of 28 models qualify: the GPT-5, GPT-4.1 and GPT-4o lines, o3 and o4-mini, all three Claude models, and four Gemini models.
  4. Llama 4 Maverick is excluded (Batch = —); Mistral Large is excluded (Caching = —); DeepSeek-V3 is excluded (Batch = —).

Which models support function calling? (Match ANY)

  1. Filter chip: Tools / function calling — Match ANY.
  2. Every one of the 28 catalogue models resolves to ✓ or ~.
  3. 27 are full ✓; DeepSeek-R1 is ~ because function calling on its reasoner endpoint is limited.
  4. Result: 28 of 28 — tool use is now table stakes across hosted LLM APIs.

Compare GPT-5 vs Claude Opus 4.8

  1. Open the compare panel and pick GPT-5 and Claude Opus 4.8.
  2. compareModels returns 14 rows; 3 differ.
  3. JSON mode: GPT-5 ✓ (schema-guaranteed) vs Claude ~ (via tool use).
  4. Fine-tuning: GPT-5 ~ (limited availability) vs Claude — (not offered).
  5. Web search: GPT-5 ~ (Responses API tool) vs Claude ✓ (native tool). All other 11 features match.

Frequently asked questions

Sources & references

Each model row in the tool links to the exact provider doc its values came from. The primary references are:

Feature values were last cross-checked against these sources on 2026-07-17. Model capabilities change frequently — always confirm against the linked provider doc before writing production code.

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Comments & feedback

Spotted a bug or want an improvement? Tell us — our team reviews every comment, and good ideas get built. Comments are public and anonymous.

Spotted a feature value that has changed, or a model we should add?

Email me at [email protected] — most fixes ship within 24 hours.