MiniMax-M2.7-highspeed vs GLM-5V-Turbo vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B comes out ahead, 58 to 49 and 41 on our weighted score.
MiniMaxMiniMax-M2.7-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- 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 GLM-5V-Turbo (49) and MiniMax-M2.7-highspeed (41). It leads on inputs & features and context window. 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-M2.7-highspeedMiniMax-M2.7-highspeed $1.05 · Qwen3.5 122B-A10B $1.10 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10BQwen3.5 122B-A10B 262,144 · MiniMax-M2.7-highspeed 204,800 · GLM-5V-Turbo 200,000 tokens
- Widest inputsGLM-5V-Turbo and Qwen3.5 122B-A10BMiniMax-M2.7-highspeed: Text · GLM-5V-Turbo: Text, Images, PDFs, Video · 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 | GLM-5V-Turbo | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 49 | 37 | 48 |
| Inputs & features | 30% | 35 | 80 | 90 |
| Context window | 20% | 32 | 32 | 37 |
| Overall | 100% | 41/100 | 49/100 | 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 | GLM-5V-TurboZ.ai (Zhipu) | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $1.20 | $0.40 (best) |
| Output | $2.40 (best) | $4.00 | $3.20 |
| Cached input | $0.06 (best) | $0.24 | — |
| Blended (3:1) | $1.05 (best) | $1.90 | $1.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Z.AI API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 200,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | 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 | Proprietary | Open |
| API model ID | MiniMax-M2.7-highspeed | glm-5v-turbo | qwen3.5-122b-a10b |
| API providers | 14 | 14 | 19 (best) |
| Released | Mar 18, 2026 | Apr 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-M2.7-highspeed$10.80
- GLM-5V-Turbo$20.00
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: MiniMax-M2.7-highspeed, GLM-5V-Turbo or Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against GLM-5V-Turbo (49) and MiniMax-M2.7-highspeed (41). It leads on inputs & features and context window. 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, GLM-5V-Turbo or Qwen3.5 122B-A10B?
MiniMax-M2.7-highspeed is cheaper at $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); GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.05 per million tokens for MiniMax-M2.7-highspeed versus $1.10 for Qwen3.5 122B-A10B (1× as much) and $1.90 for GLM-5V-Turbo (1.8× 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, GLM-5V-Turbo 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, GLM-5V-Turbo 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 200,000 for GLM-5V-Turbo. Maximum output per response: MiniMax-M2.7-highspeed up to 131,072, GLM-5V-Turbo up to 131,072, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7-highspeed accepts text; GLM-5V-Turbo accepts text, images, PDFs and video; Qwen3.5 122B-A10B accepts text, images, audio and video. GLM-5V-Turbo 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; GLM-5V-Turbo is proprietary.
Which is newer?
GLM-5V-Turbo is the newest, released Apr 1, 2026. MiniMax-M2.7-highspeed came out Mar 18, 2026; Qwen3.5 122B-A10B came out Feb 23, 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.
