Long Context AI Models Compared (100K-1M Tokens in 2026)
π Updated 2026-09-17
The 1M-context landscape has moved since this comparison was written: two entries were renamed after their stealth windows closed β Hunter Alpha is now MiMo-V2.5 and OX Alpha is now GLM 5.3 Flash.
- The price table below is a September 2026 snapshot; live per-million pricing is in the pricing calculator.
- Newest long-context entry: Union Alpha β 256K, image input; free for two days in September 2026 and revealed since as Unbiased Pareto.
- Everything current: OpenRouter model directory.
Quick Answer
Longest context (tie): Hunter Alpha (mimo-v2) and Gemini 1.5 Pro both support 1M tokens.
Best alternatives:
- Claude 3.5 Sonnet: 200K tokens (best quality)
- Llama 3.1 405B: 256K tokens (best self-host)
- Qwen 2.5 72B: 256K tokens (best value)
Full Context Ranking
| Rank | Model | Context | Price | Best For |
|---|---|---|---|---|
| 1 | Hunter Alpha (mimo-v2) | 1,048,576 tokens | $0.14/$0.28 per M | Budget long context |
| 1 | Gemini 1.5 Pro | 1,048,576 tokens | $1.25/$5 | Multimodal long context |
| 3 | Llama 3.1 405B | 256K tokens | $0.90/$0.90 | Self-hosting |
| 3 | Qwen 2.5 72B | 256K tokens | $0.35/$0.80 | Chinese support |
| 5 | Claude 3.5 Sonnet | 200K tokens | $3/$15 | Quality output |
| 6 | Command R+ | 128K tokens | $3/$15 | RAG applications |
| 6 | GPT-4o | 128K tokens | $2.50/$10 | All-rounder |
| 6 | Mistral Large | 128K tokens | $2/$6 | EU data |
| 9 | Grok-2 | 100K tokens | $5/$15 | X/Twitter integration |
| 10 | Yi-Large | 200K tokens | $3/$3 | Cost-effective |
What Can You Fit in Each Context?
1M Tokens (Hunter Alpha, Gemini 1.5 Pro)
- ~700,000 words
- Entire novel (War and Peace fits!)
- 200+ page document
- 50+ research papers
- Full codebase (100+ files)
- 10+ hours of transcripts
256K Tokens (Llama 3.1, Qwen 2.5)
- ~180,000 words
- Long novel (Lord of the Rings)
- 50+ page document
- 10-15 research papers
- Medium codebase (20-30 files)
- 2-3 hours of transcripts
200K Tokens (Claude 3.5)
- ~150,000 words
- Medium novel
- 40+ page document
- 8-12 research papers
- Medium codebase
- 2 hours of transcripts
128K Tokens (GPT-4o, Command R+, Mistral)
- ~96,000 words
- Short novel
- 25+ page document
- 5-8 research papers
- Small codebase (10-15 files)
- 1+ hour of transcripts
Accuracy at Scale
Not all models handle their max context equally well.
Needle in Haystack Test (% accuracy at context depth)
| Model | 25% | 50% | 75% | 100% |
|---|---|---|---|---|
| Hunter Alpha | 97% | 94% | 89% | 82% |
| Gemini 1.5 Pro | 96% | 93% | 87% | 79% |
| Claude 3.5 | 98% | 95% | 91% | N/A (200K max) |
| Llama 3.1 | 95% | 91% | 84% | 71% |
| GPT-4o | 96% | 92% | 86% | 74% |
Key insight: Accuracy drops at extreme context (>500K tokens). For critical tasks, stay under 500K.
Cost to Process 100 Pages
Assuming ~40K tokens for 100 pages:
| Model | Cost per 100 Pages |
|---|---|
| Hunter Alpha | $0.00 |
| Qwen 2.5 72B | $0.05 |
| Llama 3.1 405B | $0.09 |
| Mistral Large | $0.32 |
| Gemini 1.5 Pro | $0.18 |
| GPT-4o | $0.28 |
| Claude 3.5 Sonnet | $0.45 |
Speed Comparison
Tokens per Second (generation)
| Model | Speed (tokens/s) |
|---|---|
| Hunter Alpha | ~50 |
| Gemini 1.5 Pro | ~80 |
| Claude 3.5 Sonnet | ~100 |
| Llama 3.1 405B | ~90 |
| GPT-4o | ~120 |
| Qwen 2.5 72B | ~100 |
Key insight: Hunter Alpha is slower due to massive context optimization.
When Do You Actually Need 1M Context?
Worth It
- β Full book analysis
- β Complete codebase review
- β Multi-document synthesis (20+ papers)
- β Long conversation history (100+ messages)
- β Legal document suites
Overkill
- β Single article summarization (use any model)
- β Short Q&A (<10K tokens)
- β Quick code snippets
- β Email drafting
My Recommendations
For Production
- Claude 3.5 Sonnet - Best quality for <200K tokens
- Hunter Alpha - Best for >200K tokens or budget constraints
- Gemini 1.5 Pro - If you need multimodal
For Experimentation
- Hunter Alpha - Free! Try 1M context risk-free
- Llama 3.1 405B - Cheap self-hosting option
For Specific Use Cases
- Legal docs: Hunter Alpha (entire case files)
- Codebase audit: Hunter Alpha or Claude (chunked)
- Research synthesis: Gemini 1.5 Pro or Hunter Alpha
- Conversation analysis: Hunter Alpha (full history)
The Future of Context
Industry predictions:
- 2026 H2: More 1M+ context models
- 2027: 10M context becomes feasible
- 2028: Context limits become irrelevant; focus shifts to reasoning quality
The reveal, and the live catalogue read that confirmed it, are on the Union Alpha tracker.