Long-context AI models: 82 that hold a million tokens or more

Long context 1M+
Services found: 82
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
81

MiMo-V2.6-Pro-UltraSpeed

Xiaomi
Text & chatVisionAudio
$4.35 / $8.71M tokensAPI only8.7View
82

Hy4 preview

Tencent
Text & chatReasoningAdjustable thinking
$0.84 / $2.521M tokensAPI only2.52View

Browse by need

Eighty-eight models hold a million tokens or more in a single conversation - roughly 750,000 words, or an entire codebase, a full contract bundle, a multi-hour transcript. Qwen-Long stretches furthest at 10M tokens.

Long context is not free in either sense. Several vendors charge more above a threshold - Gemini 3.1 Pro doubles from $2 to $4 on input past 200K tokens. Attention quality also degrades across very long inputs, so retrieval over a well-built index often beats pasting everything in. Lean on prompt caching when the same document is queried repeatedly.

Bigger is not smarterAttention thins out across very long inputs on every model available today.
Thresholds cost moneySeveral vendors raise the rate above 200K tokens, doubling input price mid-request.
Retrieval still winsA good index usually beats pasting the whole corpus, at a fraction of the cost.

Models with this capability

How to choose

  • Use the full window when the material must be seen at once — not as a substitute for retrieval.
  • Watch for price tiers above 200K and budget accordingly.
  • Combine with caching when the same long document is queried repeatedly.
  • Check the maximum output separately; a big input window does not imply a big answer.

Common mistakes

Pasting everything by defaultMost questions need a fraction of the context and answer better without the noise.
Ignoring the output ceilingLong analyses hit max output limits well before the input window fills.

Who this suits

Legal and complianceContract bundles and regulatory texts read in one pass.
EngineeringRepository-scale refactors where cross-file context matters.
MediaMulti-hour transcripts summarised without chunking.

Frequently asked questions

Is a bigger window always better?

No. Attention quality degrades across very long inputs, and retrieval over a good index often beats pasting everything in.

Does long context cost extra?

Often. Gemini 3.1 Pro doubles input from $2 to $4 above 200K tokens, and several vendors have similar thresholds.

What is the largest window available?

Qwen-Long at 10M tokens. Most current flagships sit at 1M.

What is the largest window on the market?

Qwen-Long at 10M tokens. Most flagships sit at 1M.

Does long context slow responses?

Yes, materially. Time to first token grows with input size.

Frequently searched

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