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
1

Claude Fable 5.1

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
2

GPT-6 Astra

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
3

GPT-6.1 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
4

GPT-6 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
5

GPT-6 Luna

OpenAI
Text & chatVisionReasoning
$0.1 / $0.51.05M tokensAPI only0.5View
6

Claude Opus 5.5

Anthropic
Text & chatVisionReasoning
$4 / $201M tokensAPI only20View
7

Claude Sonnet 5.5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
8

DeepSeek V4.1 Flash

DeepSeek
Text & chatVisionReasoning
$0.3 / $1.21M tokensAPI only1.2View
9

Qwen3.8 Max Prime

Qwen
Text & chatReasoningLong context 1M+
$3.36 / $10.081M tokensAPI only10.08View
10

GLM 5.3 FlashX

Z.ai
Text & chatVisionVideo
$0.37 / $1.251M tokensAPI only1.25View
11

Ember-1

Fireworks AI
Text & chatVisionReasoning
$3 / $151.04M tokensAPI only15View
12

Claude Opus 5

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
13

Claude Fable 5

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
14

GPT-5.6 Sol

OpenAI
Text & chatVisionReasoning
$4 / $201.05M tokensAPI only20View
15

GLM 5.3

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.41.31M tokensAPI only4.4View
16

Kimi K3

Moonshot AI
Text & chatVisionVideo
$3 / $151.05M tokensAPI only15View
17

GPT-5.6 Terra

OpenAI
Text & chatVisionReasoning
$2 / $121.05M tokensAPI only12View
18

Claude Opus 4.8

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
19

GLM 5.3 Flash

Z.ai
Text & chatVisionVideo
$0.075 / $0.251.31M tokensAPI only0.25View
20

Gemini 3.8 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View

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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