AI model comparison
Mistral Large 4 vs Qwen3.8 27B
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Mistral
Mistral Large 4
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads.
- Input / 1M
- $0.68
- Output / 1M
- $2.09
- Context
- 1.05M
Qwen
Qwen3.8 27B
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
- Input / 1M
- $0.24
- Output / 1M
- $2.20
- Context
- 1M
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3.8 27B
1.5x cheaper for a typical chat
Higher intelligence score
Mistral Large 4
38.4 vs 33.7 on Artificial Analysis
Larger context window
Mistral Large 4
1.05M vs 1M 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 27B33.7Coding index
Mistral Large 4Not availableQwen3.8 27B68.1Agentic index
Mistral Large 4Not availableQwen3.8 27B45.8Pricing
Mistral Large 4 vs Qwen3.8 27B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Mistral Large 4 | Qwen3.8 27B |
|---|---|---|
| Input tokensPer 1M tokens | $0.68 | $0.24 |
| Output tokensPer 1M tokens | $2.09 | $2.20 |
| Cached input (read)Per 1M tokens | $0.07 | $0.05 |
| 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$2.40Qwen3.8 27B$1.58Coding task
30K in, 4K out
Mistral Large 4$28.76$10.46 cachedQwen3.8 27B$16$10.30 cachedLong document summary
150K in, 2K out
Mistral Large 4$106.18$14.68 cachedQwen3.8 27B$40.40$11.90 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 27B |
|---|---|---|
| Context window | 1.05M tokens | 1M tokens |
| Max output | 262K tokens | 236K tokens |
| Input types | Image, Text | Image, Text, Video |
| 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 14, 2026 |
Features
Supported features
API features available for each model.
| Metric | Mistral Large 4 | Qwen3.8 27B |
|---|---|---|
| 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 Step 5 Preview
- Mistral Large 4 vs GLM 5.3 Flash
- Mistral Large 4 vs Gemini 3.8 Flash
- Mistral Large 4 vs Gemini 3.7 Flash
- Mistral Large 4 vs Muse Spark 1.2
- Mistral Large 4 vs DeepSeek V4.1 Flash
- Mistral Large 4 vs GPT-6 Luna
- Mistral Large 4 vs MiMo-V2.6-Flash
- Mistral Large 4 vs GPT-5.6 Luna
- Mistral Large 4 vs DeepSeek V4 Pro 0813
Qwen3.8 27BView full model details- Qwen3.8 27B vs DeepSeek V4.1 Flash
- Qwen3.8 27B vs Step 5 Preview
- Qwen3.8 27B vs Hy4 preview
- Qwen3.8 27B vs DeepSeek V4 Flash 0731
- Qwen3.8 27B vs GPT-5.6 Luna
- Qwen3.8 27B vs MiniMax M3
- Qwen3.8 27B vs GLM 5.2
- Qwen3.8 27B vs DeepSeek V4 Pro 0813
- Qwen3.8 27B vs DeepSeek V4 Flash Vision Exp
- Qwen3.8 27B vs Gemini 3.6 Flash
- Qwen3.8 27B vs Muse Spark 1.1
- Qwen3.8 27B vs Gemini 3.5 Flash
- Qwen3.8 27B vs Qwen3.7 Max
- Qwen3.8 27B vs Qwen3.6 Plus
Our take
Qwen3.8 27B is 1.5x cheaper for a typical chat. Mistral Large 4 scores higher on the Artificial Analysis Intelligence Index (38.4 vs 33.7). Mistral Large 4 has the larger context window (1.05M vs 1M tokens). 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 27B cheaper?
Qwen3.8 27B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.8 27B costs $0.24 per 1M input tokens and $2.20 per 1M output tokens, while Mistral Large 4 costs $0.68 per 1M input tokens and $2.09 per 1M output tokens.
Which has a bigger context window, Mistral Large 4 or Qwen3.8 27B?
Mistral Large 4 supports up to 1.05M tokens of context, compared with 1M for Qwen3.8 27B.
Is Mistral Large 4 smarter than Qwen3.8 27B?
On the Artificial Analysis Intelligence Index, Mistral Large 4 scores 38.4 and Qwen3.8 27B scores 33.7, putting Mistral Large 4 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 27B 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 27B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Mistral Large 4 and Qwen3.8 27B at the same time. Compare the answers side by side and keep the best one.