MiniMax-M2.5-highspeed vs MiniMax-M3 vs Qwen3.5 122B-A10B
MiniMax-M3 comes out ahead, 65 to 58 and 41 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.5-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
- Our pickMiniMax
MiniMax-M3
65/100- ECI147.0
- Price$0.30 / $1.20
- Context1.05M
Alibaba (Qwen)Qwen3.5 122B-A10B
58/100- ECI—
- Price$0.40 / $3.20
- Context262K
MiniMax-M3 is our pick
MiniMax-M3 is the better all-round choice, scoring 65/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.5-highspeed (41). It leads on price and context window. 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 priceMiniMax-M3MiniMax-M3 $0.525 · MiniMax-M2.5-highspeed $1.05 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M3MiniMax-M3 1,048,576 · Qwen3.5 122B-A10B 262,144 · MiniMax-M2.5-highspeed 204,800 tokens
- Widest inputsQwen3.5 122B-A10BMiniMax-M2.5-highspeed: Text · MiniMax-M3: Text, Images, Video · 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-M2.5-highspeed | MiniMax-M3 | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 49 | 63 | 48 |
| Inputs & features | 30% | 35 | 70 | 90 |
| Context window | 20% | 32 | 61 | 37 |
| Overall | 100% | 41/100 | 65/100 | 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-M2.5-highspeedMiniMax | MiniMax-M3MiniMax | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 147.0 | — |
| ECI rank | — | #62 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 90.9% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 71.1% | — |
| Price per million tokens | |||
| Input | $0.60 | $0.30 (best) | $0.40 |
| Output | $2.40 | $1.20 (best) | $3.20 |
| Cached input | $0.06 | $0.06 | — |
| Blended (3:1) | $1.05 | $0.525 (best) | $1.10 |
| Long-context rate | Same rate | Over 512K: $0.60 / $2.40 | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official MiniMax (minimax.io) API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 131,072 tokens | 512,000 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 | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | MiniMax-M2.5-highspeed | MiniMax-M3 | qwen3.5-122b-a10b |
| API providers | 7 | 42 (best) | 19 |
| Released | Feb 13, 2026 | Jun 1, 2026 | Feb 23, 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.
- MiniMax-M2.5-highspeed$10.80
- MiniMax-M3$5.40
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: MiniMax-M2.5-highspeed, MiniMax-M3 or Qwen3.5 122B-A10B?
MiniMax-M3 is the better all-round choice, scoring 65/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.5-highspeed (41). It leads on price and context window. 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-M2.5-highspeed, MiniMax-M3 or Qwen3.5 122B-A10B?
MiniMax-M3 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). MiniMax-M2.5-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 $0.525 per million tokens for MiniMax-M3 versus $1.05 for MiniMax-M2.5-highspeed (2× as much) and $1.10 for Qwen3.5 122B-A10B (2.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2.5-highspeed has not been scored yet, MiniMax-M3 has an ECI of 147.0 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-M2.5-highspeed, MiniMax-M3 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?
MiniMax-M3 has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.5 122B-A10B and 204,800 for MiniMax-M2.5-highspeed. Maximum output per response: MiniMax-M2.5-highspeed up to 131,072, MiniMax-M3 up to 512,000, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.5-highspeed accepts text; MiniMax-M3 accepts text, images and video; 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-M3 is the newest, released Jun 1, 2026. Qwen3.5 122B-A10B came out Feb 23, 2026; MiniMax-M2.5-highspeed came out Feb 13, 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.
