# Qwen3.7 Max vs Qwen3.8 Max

As of October 21, 2026, Qwen3.7 Max costs 25% more per input token than Qwen3.8 Max ($2.50 vs $2.00 per 1M), and both have a 992K-token context window.

- Page: https://models.litellm.ai/compare/qwen3.7-max-vs-qwen3.8-max
- Qwen3.7 Max: https://models.litellm.ai/models/qwen3.7-max
- Qwen3.8 Max: https://models.litellm.ai/models/qwen3.8-max

## Side by side

| | Qwen3.7 Max | Qwen3.8 Max |
|---|---|---|
| Input, per 1M tokens | $2.50 | $2.00 |
| Output, per 1M tokens | $7.50 | $6.00 |
| Cache read, per 1M tokens | $0.50 | $0.25 |
| Cache write, per 1M tokens | $3.125 | – |
| Context window | 991,808 tokens | 991,808 tokens |
| Max output | 65,536 tokens | 131,072 tokens |
| Image input | – | Yes |
| Tool calling | Yes | Yes |
| Structured output (JSON) | Yes | Yes |
| Prompt caching | Yes | Yes |
| Reasoning | Yes | Yes |
| Providers on LiteLLM | 6 | 8 |
| Price shown is from | Alibaba Cloud Model Studio | Alibaba Cloud Model Studio |
| Added to LiteLLM | July 29, 2026 | August 7, 2026 |

Headline prices in USD per 1M tokens, from LiteLLM's model price file.

## Cheapest provider for each

- Qwen3.7 Max: Novita AI at $1.25 input per 1M tokens (`novita/qwen/qwen3.7-max`)
- Qwen3.8 Max: DeepInfra at $1.65 input per 1M tokens (`deepinfra/Qwen/Qwen3.8-Max`)

## Benchmark scores

| Benchmark | Qwen3.7 Max | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond (Reasoning and knowledge) | 90.9% | 92.7% (xhigh) |
| SimpleQA Verified (Reasoning and knowledge) | 55.8% | 45.8% (xhigh) |
| FrontierMath (tiers 1-3) (Math) | 64.6% | 74.7% (xhigh) |
| FrontierMath (tier 4) (Math) | 34.1% | 46.3% (xhigh) |
| OTIS Mock AIME 2024-2025 (Math) | 95.6% | 99.4% (xhigh) |

From the Epoch AI Benchmarking Hub (https://epoch.ai/benchmarks), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), data as of August 27, 2026: Epoch's own runs and results it collects from each benchmark's leaderboard. Higher is better.

## When to pick which

- Qwen3.8 Max: Costs 20% less per input token: $2.00 vs $2.50 per 1M.
- Qwen3.8 Max: Returns up to 131,072 tokens per response, vs 65,536.

## FAQ

### Which is cheaper, Qwen3.7 Max or Qwen3.8 Max?

Qwen3.8 Max is cheaper at 3 input tokens per output token: $3.00 per 1M tokens blended ($2.00 input, $6.00 output), versus $3.75 ($2.50 and $7.50) for Qwen3.7 Max, as of October 21, 2026.

### Which has the larger context window, Qwen3.7 Max or Qwen3.8 Max?

Both have a 991,808-token context window.

### Can I switch from Qwen3.7 Max to Qwen3.8 Max without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "dashscope/qwen3.7-max" to "dashscope/qwen3.8-max", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.