MiniMax-M2.7-highspeed vs Mistral Small 4 vs Qwen3.5 122B-A10B
Mistral Small 4 comes out ahead, 64 to 58 and 41 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.7-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
- Our pick
Mistral AIMistral Small 4
64/100- ECI—
- Price$0.15 / $0.60
- Context256K
Alibaba (Qwen)Qwen3.5 122B-A10B
58/100- ECI—
- Price$0.40 / $3.20
- Context262K
Mistral Small 4 is our pick
Mistral Small 4 is the better all-round choice, scoring 64/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.7-highspeed (41). It leads on price. Qwen3.5 122B-A10B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMistral Small 4Mistral Small 4 $0.263 · MiniMax-M2.7-highspeed $1.05 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10BQwen3.5 122B-A10B 262,144 · Mistral Small 4 256,000 · MiniMax-M2.7-highspeed 204,800 tokens
- Widest inputsQwen3.5 122B-A10BMiniMax-M2.7-highspeed: Text · Mistral Small 4: Text, Images · Qwen3.5 122B-A10B: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | MiniMax-M2.7-highspeed | Mistral Small 4 | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 49 | 77 | 48 |
| Inputs & features | 30% | 35 | 60 | 90 |
| Context window | 20% | 32 | 36 | 37 |
| Overall | 100% | 41/100 | 64/100 | 58/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MiniMax-M2.7-highspeedMiniMax | Mistral Small 4Mistral AI | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.15 (best) | $0.40 |
| Output | $2.40 | $0.60 (best) | $3.20 |
| Cached input | $0.06 | $0.015 (best) | — |
| Blended (3:1) | $1.05 | $0.263 (best) | $1.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 256,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens | 256,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yeshigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | MiniMax-M2.7-highspeed | mistral-small-2603 | qwen3.5-122b-a10b |
| API providers | 14 | 16 | 19 (best) |
| Released | Mar 18, 2026 | Mar 16, 2026 | Feb 23, 2026 |
| Knowledge cutoff | — | Jun 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- MiniMax-M2.7-highspeed$10.80
- Mistral Small 4$2.70
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: MiniMax-M2.7-highspeed, Mistral Small 4 or Qwen3.5 122B-A10B?
Mistral Small 4 is the better all-round choice, scoring 64/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.7-highspeed (41). It leads on price. Qwen3.5 122B-A10B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MiniMax-M2.7-highspeed, Mistral Small 4 or Qwen3.5 122B-A10B?
Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral API price). MiniMax-M2.7-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price); Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for Mistral Small 4 versus $1.05 for MiniMax-M2.7-highspeed (4× as much) and $1.10 for Qwen3.5 122B-A10B (4.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2.7-highspeed has not been scored yet, Mistral Small 4 has not been scored yet and Qwen3.5 122B-A10B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.7-highspeed, Mistral Small 4 and Qwen3.5 122B-A10B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 122B-A10B has the largest context window at 262,144 tokens, against 256,000 for Mistral Small 4 and 204,800 for MiniMax-M2.7-highspeed. Maximum output per response: MiniMax-M2.7-highspeed up to 131,072, Mistral Small 4 up to 256,000, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7-highspeed accepts text; Mistral Small 4 accepts text and images; Qwen3.5 122B-A10B accepts text, images, audio and video. Qwen3.5 122B-A10B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
MiniMax-M2.7-highspeed is the newest, released Mar 18, 2026. Mistral Small 4 came out Mar 16, 2026; Qwen3.5 122B-A10B came out Feb 23, 2026. Knowledge cutoff: Mistral Small 4 Jun 2025.
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.
