AIモデルインテリジェンス

機能 · 2026-05-12

ロングコンテキストに対応した AI モデル

200K トークン以上のコンテキストを扱える LLM の比較。

これは何か

  • ロングコンテキスト LLM は一度のプロンプトに 200K トークン以上を受け付けられます —— 書籍一枚、複数ファイルのコードベース、長時間の書き起こしなど。
  • 一部モデルは 1M・2M トークン、さらに大規模まで拡張します。

なぜ重要か

  • RAG の代替または補完になります —— チャンク検索の代わりに全文を貼れる場合があります。
  • 入力が長くなると実効的な想起は低下しやすく、長プロンプトは百万トークン単価で高くなりがちです。
  • 200K 超で段階価格を設けるベンダーもあります —— 詳細は各モデルページの >200K レートを参照してください。

この機能に対応するモデル 397 件

モデルベンダー入力 / 1M出力 / 1Mコンテキストプロバイダー
Gemini 1.5 Flash-8BGoogle$0.037$0.1501M1
Qwen3 235B A22B Instruct 2507Alibaba (Qwen)$0.100$0.100262K18
Qwen3-235B-A22B-Thinking-2507Alibaba (Qwen)$0.100$0.100262K17
Qwen3 30B A3B Instruct 2507Alibaba (Qwen)$0.100$0.100262K12
Qwen3 30B A3B Thinking 2507Alibaba (Qwen)$0.100$0.100262K7
Qwen/Qwen3.5-9BAlibaba (Qwen)$0.050$0.150262K6
Qwen/Qwen3-VL-30B-A3B-ThinkingAlibaba (Qwen)$0.100$0.100262K6
Qwen/Qwen3-VL-30B-A3B-InstructAlibaba (Qwen)$0.100$0.100262K6
Qwen/Qwen3-VL-8B-InstructAlibaba (Qwen)$0.100$0.100262K5
Qwen TurboAlibaba (Qwen)$0.050$0.2001M6
Amazon Nova Lite 1.0nano-gpt$0.059$0.238300K1
Amazon: Nova Lite 1.0kilo$0.060$0.240300K1
Nova Liteamazon-bedrock$0.060$0.240300K1
Nova Litevercel$0.060$0.240300K1
Ministral 8Bllmgateway$0.150$0.150262K1
inclusionAI: Ling-2.6 Flashkilo$0.080$0.240262K1
Hy3 previewopenrouter$0.066$0.260256K1
Qwen3 Coder 30B A3B InstructAlibaba (Qwen)$0.070$0.270262K3
Qwen LongAlibaba (Qwen)$0.072$0.28710M2
Seed 1.6 Flash (250715)llmgateway$0.070$0.300256K1
Gemini 2.0 Flash LiteGoogle$0.075$0.3001.05M8
ByteDance Seed: Seed 1.6 Flashkilo$0.075$0.300262K1
Gemini 1.5 FlashGoogle$0.075$0.3001M1
MiMo V2 Flash TEEchutes$0.090$0.290262K1
Step 3.5 FlashStepFun$0.096$0.288256K9
Gemma 4 26BGoogle$0.100$0.300256K8
MiMo-V2-Flashxiaomi$0.100$0.300262K7
MiMo-V2-Flashhuggingface$0.100$0.300262K1
Ling-2.6-flashnovita-ai$0.100$0.300262K1
XiaomiMiMo/MiMo-V2-Flashnovita-ai$0.100$0.300262K1
Mimo-V2-Flashqiniu-ai$0.100$0.300256K1
Step 3.5 Flash 2603StepFun$0.100$0.300256K1
MiMo V2 Flashmeganova$0.100$0.300262K1
Ministral 14Bllmgateway$0.200$0.200262K1
MiMo-V2-Flashllmgateway$0.100$0.300262K1
MiMo V2 Flash (Thinking) Originalxiaomi$0.102$0.306256K1
MiMo V2 Flash (Thinking)xiaomi$0.102$0.306256K1
MiMo V2 Flash Originalxiaomi$0.102$0.306256K1
DeepSeek V4 FlashDeepSeek$0.140$0.2801M15
DeepSeek ChatDeepSeek$0.140$0.2801M5
DeepSeek ReasonerDeepSeek$0.140$0.2801M4
GPT-5 NanoOpenAI$0.050$0.400400K17
Qwen FlashAlibaba (Qwen)$0.050$0.4001M4
Kilo Auto Smallkilo$0.050$0.400400K1
GLM-4.7-FlashZ.AI / Zhipu$0.060$0.400200K18
GLM-4.7-FlashXZ.AI / Zhipu$0.070$0.400200K6
Gemini 2.5 Flash LiteGoogle$0.100$0.4001.05M13
GPT-4.1 nanoOpenAI$0.100$0.4001.05M12
Gemini 2.5 Flash Lite Preview 09-25Google$0.100$0.4001.05M9
Gemini 2.0 FlashGoogle$0.100$0.4001.05M6
Gemini 2.5 Flash Lite Preview 06-17Google$0.100$0.4001.05M4
Gemini 2.0 FlashGoogle$0.100$0.4001.05M3
Qwen3.5 FlashAlibaba (Qwen)$0.100$0.4001M3
Gemini Flash-Lite LatestGoogle$0.100$0.4001.05M2
ByteDance Seed: Seed-2.0-Minikilo$0.100$0.400262K1
Gemma 4 31BGoogle$0.130$0.380256K11
Qwen/Qwen3-VL-32B-InstructAlibaba (Qwen)$0.104$0.416262K3
Jamba Mininano-gpt$0.199$0.408256K1
Jamba Mini 1.7nano-gpt$0.199$0.408256K1
Jamba Mini 1.6nano-gpt$0.199$0.408256K1

全 397 件中、上位 60 件を表示。 さらに絞り込むには モデル一覧 をご利用ください。

Frequently asked questions

How many AI models support 200K+ コンテキスト?

397 canonical models in our database currently support 200K+ コンテキスト. The list is regenerated on every data refresh, so it always reflects the latest model releases from models.dev.

What is the cheapest model with 200K+ コンテキスト?

Gemini 1.5 Flash-8B from Google is currently the lowest-priced option, at $0.037 per 1M input tokens and $0.150 per 1M output tokens. The full table above is sorted price-ascending.

Which model with 200K+ コンテキスト has the largest context window?

Qwen Long (Alibaba (Qwen)) leads on context at 10M tokens. This may matter if you also need long-document understanding alongside 200K+ コンテキスト.

Which models are available on the most providers?

Production-readiness usually correlates with how many independent providers host the same weights. The top three by provider count are: Kimi K2.5 (45), MiniMax-M2.5 (40), GLM-5 (38).

How is 200K+ コンテキスト different from a regular LLM?

Long-context models accept ≥ 200K input tokens — enough for entire books, codebases or hours of transcripts in one prompt. Effective recall and per-token pricing both degrade with input length, so 'big context' is not always the right choice over RAG.

How often is this list updated?

Daily. Our data pipeline pulls models.dev once a day, regenerates the canonical model list, and rebuilds these pages so newly released models appear within 24 hours.

最終更新:

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.