MiniMax-M2.7-highspeed vs Mercury 2 vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B comes out ahead, 58 to 53 and 41 on our weighted score, though Mercury 2 is 2.9× cheaper per token.
MiniMaxMiniMax-M2.7-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
InceptionMercury 2
53/100- ECI—
- Price$0.25 / $0.75
- Context128K
- Our pick
Alibaba (Qwen)Qwen3.5 122B-A10B
58/100- ECI—
- Price$0.40 / $3.20
- Context262K
Qwen3.5 122B-A10B is our pick
Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Mercury 2 (53) and MiniMax-M2.7-highspeed (41). It leads on inputs & features and context window. Mercury 2 wins on price. 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 priceMercury 2Mercury 2 $0.375 · 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 · MiniMax-M2.7-highspeed 204,800 · Mercury 2 128,000 tokens
- Widest inputsQwen3.5 122B-A10BMiniMax-M2.7-highspeed: Text · Mercury 2: Text · Qwen3.5 122B-A10B: Text, Images, Audio, Video
- Self-hostingMiniMax-M2.7-highspeed and Qwen3.5 122B-A10BPublishes downloadable weights
| Measure | Weight | MiniMax-M2.7-highspeed | Mercury 2 | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 49 | 70 | 48 |
| Inputs & features | 30% | 35 | 45 | 90 |
| Context window | 20% | 32 | 24 | 37 |
| Overall | 100% | 41/100 | 53/100 | 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 | Mercury 2Inception | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.25 (best) | $0.40 |
| Output | $2.40 | $0.75 (best) | $3.20 |
| Cached input | $0.06 | $0.025 (best) | — |
| Blended (3:1) | $1.05 | $0.375 (best) | $1.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Inception API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 50,000 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | MiniMax-M2.7-highspeed | mercury-2 | qwen3.5-122b-a10b |
| API providers | 14 | 1 | 19 (best) |
| Released | Mar 18, 2026 | Feb 24, 2026 | Feb 23, 2026 |
| Knowledge cutoff | — | Jan 1, 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
- Mercury 2$4.00
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: MiniMax-M2.7-highspeed, Mercury 2 or Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Mercury 2 (53) and MiniMax-M2.7-highspeed (41). It leads on inputs & features and context window. Mercury 2 wins on price. 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, Mercury 2 or Qwen3.5 122B-A10B?
Mercury 2 is cheaper at $0.25 input / $0.75 output per million tokens (official Inception 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 $0.375 per million tokens for Mercury 2 versus $1.05 for MiniMax-M2.7-highspeed (2.8× as much) and $1.10 for Qwen3.5 122B-A10B (2.9× 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, Mercury 2 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, Mercury 2 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 204,800 for MiniMax-M2.7-highspeed and 128,000 for Mercury 2. Maximum output per response: MiniMax-M2.7-highspeed up to 131,072, Mercury 2 up to 50,000, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7-highspeed accepts text; Mercury 2 accepts text; 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?
MiniMax-M2.7-highspeed and Qwen3.5 122B-A10B publishes its weights and can be self-hosted; Mercury 2 is proprietary.
Which is newer?
MiniMax-M2.7-highspeed is the newest, released Mar 18, 2026. Mercury 2 came out Feb 24, 2026; Qwen3.5 122B-A10B came out Feb 23, 2026. Knowledge cutoff: Mercury 2 Jan 1, 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.
