AI model comparison
Qwen3.8 27B vs MiniMax M3
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen
Qwen3.8 27B
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
- Input / 1M
- $0.43
- Output / 1M
- $2.55
- Context
- 1M
MiniMax
MiniMax M3
MiniMax-M3 is a multimodal foundation model from MiniMax.
- Input / 1M
- $0.30
- Output / 1M
- $1.20
- Context
- 1.05M
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
MiniMax M3
1.8x cheaper for a typical chat
Higher intelligence score
Qwen3.8 27B
33.7 vs 29.2 on Artificial Analysis
Larger context window
MiniMax M3
1.05M vs 1M tokens
Newer release
Qwen3.8 27B
Released August 14, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Qwen3.8 27B vs MiniMax M3 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.43 | $0.30 |
| Output tokensPer 1M tokens | $2.55 | $1.20 |
| Cached input (read)Per 1M tokens | $0.09 | $0.06 |
| Cache writePer 1M tokens | $0.53 | 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
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1M tokens | 1.05M tokens |
| Max output | 131K tokens | 512K tokens |
| Input types | Image, Text, Video | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Extra high, Medium, Low | Not available |
| Default reasoning effort | Extra high | Not available |
| Release date | August 14, 2026 | May 31, 2026 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| 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 |
Our take
MiniMax M3 is 1.8x cheaper for a typical chat. Qwen3.8 27B scores higher on the Artificial Analysis Intelligence Index (33.7 vs 29.2). MiniMax M3 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 Qwen3.8 27B or MiniMax M3 cheaper?
MiniMax M3 is cheaper for a typical chat (2K input tokens and 500 output tokens). MiniMax M3 costs $0.30 per 1M input tokens and $1.20 per 1M output tokens, while Qwen3.8 27B costs $0.43 per 1M input tokens and $2.55 per 1M output tokens.
Which has a bigger context window, Qwen3.8 27B or MiniMax M3?
MiniMax M3 supports up to 1.05M tokens of context, compared with 1M for Qwen3.8 27B.
Is Qwen3.8 27B smarter than MiniMax M3?
On the Artificial Analysis Intelligence Index, Qwen3.8 27B scores 33.7 and MiniMax M3 scores 29.2, putting Qwen3.8 27B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3.8 27B and MiniMax M3 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3.8 27B and MiniMax M3 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.8 27B and MiniMax M3 at the same time. Compare the answers side by side and keep the best one.