Best AI Models for Long Context
Ranking of language models by long-context capability. These models can process entire books, large codebases, and lengthy documents.Updated August 2026. Based on independent benchmark data.
Why This Matters
Choosing the right model for long context is about more than raw benchmark scores. The models below are ranked using a weighted blend of category-specific benchmarks, arena Elo, and the intelligence index — but real-world performance depends on your context window, latency budget, and integration path.
For long context, we weighted the benchmarks that most strongly predict success in production: task accuracy first, then speed and cost efficiency. Leaders on this page consistently outperform on both standardized tests and real-world workloads.
If you operate under a strict budget, check the Best Value LLMs ranking. If latency matters more than raw quality, see Fastest LLMs. Both pages use the same underlying dataset with different weightings.
| # | Model | Provider | Score | Speed | Price (output) |
|---|---|---|---|---|---|
| 1 | GPT-6 Astra (xhigh) | OpenAI | 100.0 | 76 t/s | $50/M |
| 2 | GPT-6 Astra | OpenAI | 100.0 | 82 t/s | $50/M |
| 3 | GPT-6 Astra (high) | OpenAI | 100.0 | 90 t/s | $50/M |
| 4 | GPT-6 Astra (medium) | OpenAI | 100.0 | 98 t/s | $50/M |
| 5 | GPT-5.6 Sol | OpenAI | 100.0 | 72 t/s | $30/M |
| 6 | GPT-6 Astra (low) | OpenAI | 100.0 | 110 t/s | $50/M |
| 7 | GPT-5.4 | OpenAI | 100.0 | 60 t/s | $10/M |
| 8 | Claude Fable 5 | Anthropic | 99.2 | 71 t/s | $50/M |
| 9 | Kimi K3 | Moonshot AI | 99.2 | 37 t/s | $15/M |
| 10 | Claude Opus 5 | Anthropic | 99.2 | 60 t/s | $25/M |
| 11 | Qwen3.8 Max | Alibaba | 99.2 | 55 t/s | $2/M |
| 12 | Claude Opus 4.8 | Anthropic | 99.2 | 50 t/s | $15/M |
| 13 | Muse Spark 1.1 | Meta | 99.2 | 208 t/s | $4.25/M |
| 14 | Gemini 3.6 Flash | 99.2 | 233 t/s | $7.5/M | |
| 15 | Claude Opus 4.7 | Anthropic | 99.2 | 80 t/s | $15/M |
| 16 | Qwen3.7 Max | Alibaba | 99.2 | 203 t/s | $7.5/M |
| 17 | Gemini 3.5 Flash | 99.2 | 267 t/s | $9/M | |
| 18 | MiMo V2.5 Pro | Xiaomi | 99.2 | 65 t/s | $0.87/M |
| 19 | DeepSeek V4 Pro | DeepSeek | 99.2 | 66 t/s | $0.87/M |
| 20 | Claude Sonnet 5 | Anthropic | 99.2 | 96 t/s | $10/M |
Top 5 Long Context — Quick Comparison
Methodology
Rankings are based on independent benchmark evaluations. The long context score is computed from multiple standardized benchmarks and normalized to 0–100. Data is updated regularly from public benchmark results.
Related Rankings
Frequently Asked Questions
Which AI model is best for long context and large documents?
Gemini 2.0 Pro (2M tokens) and Claude 3.7 Sonnet (200K tokens) lead in large codebase analysis and document retrieval.