MiniMax-M2.1 vs MiniMax-M2 Her vs GLM-4.6V
GLM-4.6V comes out ahead, 59 to 48 and 45 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.1
48/100- ECI—
- Price$0.30 / $1.20
- Context205K
- MiniMax
MiniMax-M2 Her
45/100- ECI—
- Price$0.30 / $1.20
- Context66K
- Our pick
Z.ai (Zhipu)GLM-4.6V
59/100- ECI—
- Price$0.30 / $0.90
- Context128K
GLM-4.6V is our pick
GLM-4.6V is the better all-round choice, scoring 59/100 against MiniMax-M2.1 (48) and MiniMax-M2 Her (45). It leads on price and inputs & features. MiniMax-M2.1 wins on 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 priceGLM-4.6VGLM-4.6V $0.45 · MiniMax-M2.1 $0.525 · MiniMax-M2 Her $0.525 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.1MiniMax-M2.1 204,800 · GLM-4.6V 128,000 · MiniMax-M2 Her 65,536 tokens
- Widest inputsGLM-4.6VMiniMax-M2.1: Text · MiniMax-M2 Her: Text · GLM-4.6V: Text, Images, Video
- Self-hostingMiniMax-M2.1 and GLM-4.6VPublishes downloadable weights
| Measure | Weight | MiniMax-M2.1 | MiniMax-M2 Her | GLM-4.6V |
|---|---|---|---|---|
| Price | 50% | 63 | 63 | 66 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 32 | 12 | 24 |
| Overall | 100% | 48/100 | 45/100 | 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-M2.1MiniMax | MiniMax-M2 HerMiniMax | GLM-4.6VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.30 | $0.30 |
| Output | $1.20 | $1.20 | $0.90 (best) |
| Cached input | $0.03 | — | — |
| Blended (3:1) | $0.525 | $0.525 | $0.45 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Median of 4 providers | Official Z.AI API |
| Limits | |||
| Context window | 204,800 tokens (best) | 65,536 tokens | 128,000 tokens |
| Max output | 131,072 tokens (best) | 2,048 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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-M2.1 | — | glm-4.6v |
| API providers | 13 (best) | 4 | 10 |
| Released | Dec 23, 2025 | Jan 23, 2026 | Dec 8, 2025 |
| Knowledge cutoff | — | — | 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-M2.1$5.40
- MiniMax-M2 Her$5.40
- GLM-4.6V$4.80
Which should you choose?
Which is better: MiniMax-M2.1, MiniMax-M2 Her or GLM-4.6V?
GLM-4.6V is the better all-round choice, scoring 59/100 against MiniMax-M2.1 (48) and MiniMax-M2 Her (45). It leads on price and inputs & features. MiniMax-M2.1 wins on 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-M2.1, MiniMax-M2 Her 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-M2.1 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price); MiniMax-M2 Her costs $0.30 input / $1.20 output per million tokens (median across 4 API providers). 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 (1.2× as much) and $0.525 for MiniMax-M2 Her (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2.1 has not been scored yet, MiniMax-M2 Her 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-M2.1, MiniMax-M2 Her 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?
MiniMax-M2.1 has the largest context window at 204,800 tokens, against 128,000 for GLM-4.6V and 65,536 for MiniMax-M2 Her. Maximum output per response: MiniMax-M2.1 up to 131,072, MiniMax-M2 Her up to 2,048, GLM-4.6V up to 32,768 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.1 accepts text; MiniMax-M2 Her accepts text; GLM-4.6V accepts text, images and video. GLM-4.6V handles the widest range of inputs.
Are any of these open source?
MiniMax-M2.1 and GLM-4.6V publishes its weights and can be self-hosted; MiniMax-M2 Her is proprietary.
Which is newer?
MiniMax-M2 Her is the newest, released Jan 23, 2026. MiniMax-M2.1 came out Dec 23, 2025; GLM-4.6V came out Dec 8, 2025. Knowledge cutoff: 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.
