AI model comparison
Qwen3.8 27B vs MiMo-V2.5-Pro
Side by side comparison of Qwen3.8 27B and MiMo-V2.5-Pro on pricing, benchmark scores, context window, and more.
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
- Input / 1M
- $0.15
- Output / 1M
- $1.88
- Context
- 1.02M
MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro.
- Input / 1M
- $0.48
- Output / 1M
- $1.80
- 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
Qwen3.8 27B
1.5x cheaper for a typical chat
Higher intelligence score
Not available
Not enough benchmark data
Larger context window
MiMo-V2.5-Pro
1.05M vs 1.02M tokens
Newer release
Qwen3.8 27B
Released August 14, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.8 27B20.1Coding index
Qwen3.8 27B68.1Agentic index
Qwen3.8 27B45.8Pricing
Qwen3.8 27B vs MiMo-V2.5-Pro API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.15 | $0.48 |
| Output tokensPer 1M tokens | $1.88 | $1.80 |
| Cached input (read)Per 1M tokens | $0.04 | $0.10 |
| 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
Qwen3.8 27B$1.24Coding task
30K in, 4K out
Qwen3.8 27B$12$8.63 cachedLong document summary
150K in, 2K out
Qwen3.8 27B$26.25$9.38 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Context window | 1.02M tokens | 1.05M tokens |
| Max output | 236K tokens | 236K tokens |
| Input types | Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Extra high, Medium, Low, None | Not available |
| Default reasoning effort | Extra high | Not available |
| Release date | August 14, 2026 | April 22, 2026 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Not 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.
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- Qwen3.8 27B vs Inkling
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- Qwen3.8 27B vs Gemini 3.5 Flash Lite
- Qwen3.8 27B vs Step 3.7 Flash
- Qwen3.8 27B vs Qwen3.6 35B A3B
- Qwen3.8 27B vs MiMo-V2.5
Our take
Qwen3.8 27B is 1.5x cheaper for a typical chat. MiMo-V2.5-Pro has the larger context window (1.05M vs 1.02M 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 Qwen3.8 27B or MiMo-V2.5-Pro cheaper?
Qwen3.8 27B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.8 27B costs $0.15 per 1M input tokens and $1.88 per 1M output tokens, while MiMo-V2.5-Pro costs $0.48 per 1M input tokens and $1.80 per 1M output tokens.
Which has a bigger context window, Qwen3.8 27B or MiMo-V2.5-Pro?
MiMo-V2.5-Pro supports up to 1.05M tokens of context, compared with 1.02M for Qwen3.8 27B.
Can I use Qwen3.8 27B and MiMo-V2.5-Pro at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3.8 27B and MiMo-V2.5-Pro answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.8 27B and MiMo-V2.5-Pro at the same time. Compare the answers side by side and keep the best one.