AI model comparison
MiMo-V2.6-Flash vs Qwen3.8 27B
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
MiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi.
- Input / 1M
- $0.14
- Output / 1M
- $0.28
- Context
- 1.05M
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
- Input / 1M
- $0.04
- Output / 1M
- $1.35
- Context
- 1M
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
MiMo-V2.6-Flash
1.8x cheaper for a typical chat
Higher intelligence score
MiMo-V2.6-Flash
37.9 vs 33.7 on Artificial Analysis
Larger context window
MiMo-V2.6-Flash
1.05M vs 1M tokens
Newer release
MiMo-V2.6-Flash
Released September 21, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.8 27B33.7Coding index
Qwen3.8 27B68.1Agentic index
Qwen3.8 27B45.8Pricing
MiMo-V2.6-Flash vs Qwen3.8 27B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.14 | $0.04 |
| Output tokensPer 1M tokens | $0.28 | $1.35 |
| Cached input (read)Per 1M tokens | $0.00 | $0.02 |
| 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$0.76Coding task
30K in, 4K out
Qwen3.8 27B$6.60$5.94 cachedLong document summary
150K in, 2K out
Qwen3.8 27B$8.70$5.40 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 | 1.05M tokens | 1M tokens |
| Max output | 131K tokens | 66K tokens |
| Input types | Audio, Image, Text, Video | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Extra high, Medium, Low, None |
| Default reasoning effort | Not available | Extra high |
| Release date | September 21, 2026 | August 14, 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 | 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.
- MiMo-V2.6-Flash vs DeepSeek V4.1 Flash
- MiMo-V2.6-Flash vs GLM 5.3 Flash
- MiMo-V2.6-Flash vs DeepSeek V4.1 Flash 1017
- MiMo-V2.6-Flash vs Hy4 preview
- MiMo-V2.6-Flash vs Step 5 Preview
- MiMo-V2.6-Flash vs Claude Opus 5.5
- MiMo-V2.6-Flash vs GPT-6 Luna
- MiMo-V2.6-Flash vs GLM 5.3
- MiMo-V2.6-Flash vs DeepSeek V4 Flash 0731
- MiMo-V2.6-Flash vs Hy3
- MiMo-V2.6-Flash vs Muse Spark 1.3 Contributor
- MiMo-V2.6-Flash vs Claude Sonnet 5.5
- MiMo-V2.6-Flash vs Claude Haiku 5.5
- MiMo-V2.6-Flash vs GPT-6.1 Sol
- MiMo-V2.6-Flash vs MiMo-V2.6-Pro
- MiMo-V2.6-Flash vs GPT-5.6 Luna
- MiMo-V2.6-Flash vs DeepSeek V4 Pro 0813
- MiMo-V2.6-Flash vs Gemini 4 Argon
- MiMo-V2.6-Flash vs Claude Fable 5.1
- MiMo-V2.6-Flash vs GPT-6 Astra
- MiMo-V2.6-Flash vs Qwen3.8 Flash
- MiMo-V2.6-Flash vs GPT-6 Luna Pro
- MiMo-V2.6-Flash vs Qwen3.7 Flash
- MiMo-V2.6-Flash vs Ling 3.1 Flash
- MiMo-V2.6-Flash vs Mistral Nemo
- MiMo-V2.6-Flash vs Mistral Large 4
- MiMo-V2.6-Flash vs DeepSeek V4 Flash Vision Exp
Qwen3.8 27BView full model details- Qwen3.8 27B vs DeepSeek V4.1 Flash 1017
- Qwen3.8 27B vs GPT-6 Luna
- 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 DeepSeek V4 Pro 0423
- Qwen3.8 27B vs Gemini 3.6 Flash
- Qwen3.8 27B vs Muse Spark 1.1
- Qwen3.8 27B vs Qwen3.7 Max
Our take
MiMo-V2.6-Flash is 1.8x cheaper for a typical chat. MiMo-V2.6-Flash scores higher on the Artificial Analysis Intelligence Index (37.9 vs 33.7). MiMo-V2.6-Flash 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 MiMo-V2.6-Flash or Qwen3.8 27B cheaper?
MiMo-V2.6-Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). MiMo-V2.6-Flash costs $0.14 per 1M input tokens and $0.28 per 1M output tokens, while Qwen3.8 27B costs $0.04 per 1M input tokens and $1.35 per 1M output tokens.
Which has a bigger context window, MiMo-V2.6-Flash or Qwen3.8 27B?
MiMo-V2.6-Flash supports up to 1.05M tokens of context, compared with 1M for Qwen3.8 27B.
Is MiMo-V2.6-Flash smarter than Qwen3.8 27B?
On the Artificial Analysis Intelligence Index, MiMo-V2.6-Flash scores 37.9 and Qwen3.8 27B scores 33.7, putting MiMo-V2.6-Flash ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use MiMo-V2.6-Flash and Qwen3.8 27B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiMo-V2.6-Flash and Qwen3.8 27B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiMo-V2.6-Flash and Qwen3.8 27B at the same time. Compare the answers side by side and keep the best one.