MiniMax-M2 vs Qwen3-VL Plus vs GLM-4.6V
Too close to call on our weighted score (GLM-4.6V 59, Qwen3-VL Plus 56, MiniMax-M2 48). The right pick depends on what you value most.
MiniMaxMiniMax-M2
48/100- ECI—
- Price$0.30 / $1.20
- Context205K
Alibaba (Qwen)Qwen3-VL Plus
56/100- ECI—
- Price$0.20 / $1.60
- Context262K
Z.ai (Zhipu)GLM-4.6V
59/100- ECI—
- Price$0.30 / $0.90
- Context128K
Too close to call
It is close. Our weighted score puts them within 3 points (GLM-4.6V 59/100, Qwen3-VL Plus 56/100, MiniMax-M2 48/100), so choose by what matters most for your work: GLM-4.6V on price and Qwen3-VL Plus for long inputs. 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 priceGLM-4.6VGLM-4.6V $0.45 · MiniMax-M2 $0.525 · Qwen3-VL Plus $0.55 per 1M tokens (3:1 blend)
- Longest contextQwen3-VL PlusQwen3-VL Plus 262,144 · MiniMax-M2 204,800 · GLM-4.6V 128,000 tokens
- Widest inputsGLM-4.6VMiniMax-M2: Text · Qwen3-VL Plus: Text, Images · GLM-4.6V: Text, Images, Video
- Self-hostingMiniMax-M2 and GLM-4.6VPublishes downloadable weights
| Measure | Weight | MiniMax-M2 | Qwen3-VL Plus | GLM-4.6V |
|---|---|---|---|---|
| Price | 50% | 63 | 62 | 66 |
| Inputs & features | 30% | 35 | 60 | 70 |
| Context window | 20% | 32 | 37 | 24 |
| Overall | 100% | 48/100 | 56/100 | 59/100 |
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-M2MiniMax | Qwen3-VL PlusAlibaba (Qwen) | GLM-4.6VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.20 (best) | $0.30 |
| Output | $1.20 | $1.60 | $0.90 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.525 | $0.55 | $0.45 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Alibaba API | Official Z.AI API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | MiniMax-M2 | qwen3-vl-plus | glm-4.6v |
| API providers | 13 (best) | 6 | 10 |
| Released | Oct 27, 2025 | Sep 23, 2025 | Dec 8, 2025 |
| Knowledge cutoff | — | Apr 2025 | Apr 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$5.40
- Qwen3-VL Plus$5.20
- GLM-4.6V$4.80
Which should you choose?
Which is better: MiniMax-M2, Qwen3-VL Plus or GLM-4.6V?
It is close. Our weighted score puts them within 3 points (GLM-4.6V 59/100, Qwen3-VL Plus 56/100, MiniMax-M2 48/100), so choose by what matters most for your work: GLM-4.6V on price and Qwen3-VL Plus for long inputs. 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, Qwen3-VL Plus or GLM-4.6V?
GLM-4.6V is cheaper at $0.30 input / $0.90 output per million tokens (official Z.AI API price). MiniMax-M2 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price); Qwen3-VL Plus costs $0.20 input / $1.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.45 per million tokens for GLM-4.6V versus $0.525 for MiniMax-M2 (1.2× as much) and $0.55 for Qwen3-VL Plus (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2 has not been scored yet, Qwen3-VL Plus has not been scored yet and GLM-4.6V has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2, Qwen3-VL Plus and GLM-4.6V 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-VL Plus has the largest context window at 262,144 tokens, against 204,800 for MiniMax-M2 and 128,000 for GLM-4.6V. Maximum output per response: MiniMax-M2 up to 131,072, Qwen3-VL Plus up to 32,768, GLM-4.6V up to 32,768 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2 accepts text; Qwen3-VL Plus accepts text and images; GLM-4.6V accepts text, images and video. GLM-4.6V handles the widest range of inputs.
Are any of these open source?
MiniMax-M2 and GLM-4.6V publishes its weights and can be self-hosted; Qwen3-VL Plus is proprietary.
Which is newer?
GLM-4.6V is the newest, released Dec 8, 2025. MiniMax-M2 came out Oct 27, 2025; Qwen3-VL Plus came out Sep 23, 2025. Knowledge cutoff: Qwen3-VL Plus Apr 2025, GLM-4.6V Apr 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.
