Qwen3.6 27B vs MiniMax-M3
MiniMax-M3 comes out ahead, 69 to 65 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.6 27B
65/100- ECI146.5
- Price$0.60 / $3.60
- Context262K
- Our pick
MiniMaxMiniMax-M3
69/100- ECI147.0
- Price$0.30 / $1.20
- Context1.05M
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MiniMax-M3 is our pick
MiniMax-M3 is the better all-round choice, scoring 69/100 against Qwen3.6 27B (65). It leads on price and context window. Qwen3.6 27B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M3Capabilities Index (ECI): MiniMax-M3 147.0 · Qwen3.6 27B 146.5
- Lowest priceMiniMax-M3MiniMax-M3 $0.525 · Qwen3.6 27B $1.35 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M3MiniMax-M3 1,048,576 · Qwen3.6 27B 262,144 tokens
- Widest inputsQwen3.6 27BQwen3.6 27B: Text, Images, Audio, Video · MiniMax-M3: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.6 27B | MiniMax-M3 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 74 | 74 |
| Price | 25% | 44 | 63 |
| Inputs & features | 15% | 90 | 70 |
| Context window | 10% | 37 | 61 |
| Overall | 100% | 65/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.6 27BAlibaba (Qwen) | MiniMax-M3MiniMax |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 146.5 | 147.0 (best) |
| ECI rank | #68 of 148 | #62 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 85.9% | 90.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 35.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% (best) | 71.1% |
| Price per million tokens | ||
| Input | $0.60 | $0.30 (best) |
| Output | $3.60 | $1.20 (best) |
| Cached input | — | $0.06 |
| Blended (3:1) | $1.35 | $0.525 (best) |
| Long-context rate | Same rate | Over 512K: $0.60 / $2.40 |
| Price source | Official Alibaba API | Official MiniMax (minimax.io) API |
| Limits | ||
| Context window | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 65,536 tokens | 512,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | Yes | No |
| Video | Yes | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | qwen3.6-27b | MiniMax-M3 |
| API providers | 27 | 42 (best) |
| Released | Apr 22, 2026 | Jun 1, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.6 27B$13.20
- MiniMax-M3$5.40
Which should you choose?
Which is better: Qwen3.6 27B or MiniMax-M3?
MiniMax-M3 is the better all-round choice, scoring 69/100 against Qwen3.6 27B (65). It leads on price and context window. Qwen3.6 27B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.6 27B or MiniMax-M3?
MiniMax-M3 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). Qwen3.6 27B costs $0.60 input / $3.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M3 versus $1.35 for Qwen3.6 27B (2.6× as much).
Which scores higher on benchmarks?
MiniMax-M3 scores higher on the Capabilities Index (ECI): MiniMax-M3 147.0 (#62 of 148) and Qwen3.6 27B 146.5 (#68 of 148). The confidence ranges of the top two overlap (142.7–149.8 vs 144.2–147.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — MiniMax-M3 90.9%, Qwen3.6 27B 85.9%; OTIS Mock AIME 2024–2025 — Qwen3.6 27B 91.1%, MiniMax-M3 71.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.6 27B and MiniMax-M3 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M3 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
MiniMax-M3 has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.6 27B. Maximum output per response: Qwen3.6 27B up to 65,536, MiniMax-M3 up to 512,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3.6 27B accepts text, images, audio and video; MiniMax-M3 accepts text, images and video. Qwen3.6 27B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
MiniMax-M3 is the newest, released Jun 1, 2026. Qwen3.6 27B came out Apr 22, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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