AI model comparison
Mistral Large 4 vs Qwen3.8 2.4T A95B
Side by side comparison of Mistral Large 4 and Qwen3.8 2.4T A95B on pricing, benchmark scores, context window, and more.
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads.
- Input / 1M
- $1.36
- Output / 1M
- $4.18
- Context
- 1.05M
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total.
- Input / 1M
- $2
- Output / 1M
- $6
- Context
- 1.05M
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Mistral Large 4
1.5x cheaper for a typical chat
Higher intelligence score
Qwen3.8 2.4T A95B
39.9 vs 38.4 on Artificial Analysis
Larger context window
Tie
1.05M vs 1.05M tokens
Newer release
Mistral Large 4
Released October 6, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Mistral Large 438.4Qwen3.8 2.4T A95B39.9Coding index
Mistral Large 4Not availableQwen3.8 2.4T A95B71.9Agentic index
Mistral Large 4Not availableQwen3.8 2.4T A95B50.1Pricing
Mistral Large 4 vs Qwen3.8 2.4T A95B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Mistral Large 4 | Qwen3.8 2.4T A95B |
|---|---|---|
| Input tokensPer 1M tokens | $1.36 | $2 |
| Output tokensPer 1M tokens | $4.18 | $6 |
| Cached input (read)Per 1M tokens | $0.14 | $0.25 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Mistral Large 4$4.81Qwen3.8 2.4T A95B$7Coding task
30K in, 4K out
Mistral Large 4$57.52$20.92 cachedQwen3.8 2.4T A95B$84$31.50 cachedLong document summary
150K in, 2K out
Mistral Large 4$212.36$29.36 cachedQwen3.8 2.4T A95B$312$49.50 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Mistral Large 4 | Qwen3.8 2.4T A95B |
|---|---|---|
| Context window | 1.05M tokens | 1.05M tokens |
| Max output | 262K tokens | 909K tokens |
| Input types | Image, Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | High, None | Extra high, Medium, Low |
| Default reasoning effort | High | Extra high |
| Release date | October 6, 2026 | August 12, 2026 |
Features
Supported features
API features available for each model.
| Metric | Mistral Large 4 | Qwen3.8 2.4T A95B |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
Mistral Large 4View full model details- Mistral Large 4 vs Gemini 3.8 Flash
- Mistral Large 4 vs Gemini 3.7 Flash
- Mistral Large 4 vs DeepSeek V4.1 Flash 1017
- Mistral Large 4 vs Muse Spark 1.2
- Mistral Large 4 vs Grok 4.5
- Mistral Large 4 vs GPT-5.5
- Mistral Large 4 vs Claude Sonnet 5
- Mistral Large 4 vs GPT-6 Luna
- Mistral Large 4 vs GPT-5.6 Luna
- Mistral Large 4 vs DeepSeek V4 Pro 0813
- Mistral Large 4 vs Gemini 3.6 Flash
- Mistral Large 4 vs Muse Spark 1.1
Qwen3.8 2.4T A95BView full model details- Qwen3.8 2.4T A95B vs Qwen3.8 Max (0902)
- Qwen3.8 2.4T A95B vs Step 5 Preview
- Qwen3.8 2.4T A95B vs Kimi K3
- Qwen3.8 2.4T A95B vs Gemini 3.8 Flash
- Qwen3.8 2.4T A95B vs Gemini 3.7 Flash
- Qwen3.8 2.4T A95B vs Muse Spark 1.2
- Qwen3.8 2.4T A95B vs DeepSeek V4.1 Flash 1017
- Qwen3.8 2.4T A95B vs Grok 4.5
- Qwen3.8 2.4T A95B vs Claude Sonnet 5
Our take
Mistral Large 4 is 1.5x cheaper for a typical chat. Qwen3.8 2.4T A95B scores higher on the Artificial Analysis Intelligence Index (39.9 vs 38.4). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Mistral Large 4 or Qwen3.8 2.4T A95B cheaper?
Mistral Large 4 is cheaper for a typical chat (2K input tokens and 500 output tokens). Mistral Large 4 costs $1.36 per 1M input tokens and $4.18 per 1M output tokens, while Qwen3.8 2.4T A95B costs $2 per 1M input tokens and $6 per 1M output tokens.
Which has a bigger context window, Mistral Large 4 or Qwen3.8 2.4T A95B?
Mistral Large 4 supports up to 1.05M tokens of context, compared with 1.05M for Qwen3.8 2.4T A95B.
Is Mistral Large 4 smarter than Qwen3.8 2.4T A95B?
On the Artificial Analysis Intelligence Index, Mistral Large 4 scores 38.4 and Qwen3.8 2.4T A95B scores 39.9, putting Qwen3.8 2.4T A95B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Mistral Large 4 and Qwen3.8 2.4T A95B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Mistral Large 4 and Qwen3.8 2.4T A95B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Mistral Large 4 and Qwen3.8 2.4T A95B at the same time. Compare the answers side by side and keep the best one.