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
61

GPT-5.6 Sol Pro

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
62

GPT-6 Astra Pro

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
63

Claude Opus 4.7

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
64

Qwen3.5-Flash

Qwen
Text & chatVisionVideo
$0.065 / $0.261M tokensAPI only0.26View
65

Grok 4.20

xAI
Text & chatVisionReasoning
$1.25 / $2.52M tokensAPI only2.5View
66

GPT-5.6 Terra Pro

OpenAI
Text & chatVisionReasoning
$2 / $121.05M tokensAPI only12View
67

Qwen3.6 Plus

Qwen
Text & chatVisionVideo
$0.325 / $1.951M tokensAPI only1.95View
68

Qwen3.6 Flash

Qwen
Text & chatVisionVideo
$0.1875 / $1.1251M tokensAPI only1.125View
69

Qwen3 Coder Flash

Qwen
Text & chatVisionCoding
$0.195 / $0.9751M tokensAPI only0.975View
70

Qwen3.5 Plus 2026-02-15

Qwen
Text & chatVisionVideo
$0.26 / $1.561M tokensAPI only1.56View
71

Qwen3.5 Plus 2026-04-20

Qwen
Text & chatVisionVideo
$0.3 / $1.81M tokensAPI only1.8View
72

Qwen3 Coder Plus

Qwen
Text & chatCodingReasoning
$0.65 / $3.251M tokensAPI only3.25View
73

GPT-5.5 Pro

OpenAI
Text & chatVisionReasoning
$30 / $1801.05M tokensAPI only180View
74

Fugu Ultra

Sakana
Text & chatVisionLong context 1M+
$5 / $301M tokensAPI only30View
75

GPT-5.4 Pro

OpenAI
Text & chatVisionReasoning
$30 / $1801.05M tokensAPI only180View
76

Llama 4 Maverick

Meta
Text & chatVisionLong context 1M+
$0.2 / $0.6961.05M tokensAPI only0.696View
77

Llama 4 Scout

Meta
Text & chatVisionLong context 1M+
$0.1 / $0.310M tokensAPI only0.3View
78

Qwen3.8 Omni Flash

Qwen
Text & chatVisionAudio
1M tokensAPI onlyView
79

MiMo-V2.6-Pro

Xiaomi
Text & chatVisionAudio
$0.435 / $0.871M tokensAPI only0.87View
80

MiMo-V2.6-Flash

Xiaomi
Text & chatVisionAudio
$0.14 / $0.281M tokensAPI only0.28View

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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