GLM-4.5V vs MiniMax M1 80K
Too close to call on our weighted score (GLM-4.5V 48, MiniMax M1 80K 47). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5V
48/100- ECI—
- Price$0.60 / $1.80
- Context64K
MiniMaxMiniMax M1 80K
47/100- ECI—
- Price$0.55 / $2.20
- Context1M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (GLM-4.5V 48/100, MiniMax M1 80K 47/100), so choose by what matters most for your work: GLM-4.5V on price and MiniMax M1 80K 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-4.5VGLM-4.5V $0.90 · MiniMax M1 80K $0.963 per 1M tokens (3:1 blend)
- Longest contextMiniMax M1 80KMiniMax M1 80K 1,000,000 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · MiniMax M1 80K: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.5V | MiniMax M1 80K |
|---|---|---|---|
| Price | 50% | 50 | 48 |
| Inputs & features | 30% | 70 | 35 |
| Context window | 20% | 12 | 60 |
| Overall | 100% | 48/100 | 47/100 |
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 | GLM-4.5VZ.ai (Zhipu) | MiniMax M1 80KMiniMax |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.60 | $0.55 (best) |
| Output | $1.80 (best) | $2.20 |
| Cached input | $0.11 | — |
| Blended (3:1) | $0.90 (best) | $0.963 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 5 providers |
| Limits | ||
| Context window | 64,000 tokens | 1,000,000 tokens (best) |
| Max output | 16,384 tokens | 80,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache-2.0 |
| API model ID | glm-4.5v | — |
| API providers | 17 (best) | 5 |
| Released | Aug 11, 2025 | Jun 17, 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.
- GLM-4.5V$9.60
- MiniMax M1 80K$9.90
Which should you choose?
Which is better: GLM-4.5V or MiniMax M1 80K?
It is close. Our weighted score puts them within 2 points (GLM-4.5V 48/100, MiniMax M1 80K 47/100), so choose by what matters most for your work: GLM-4.5V on price and MiniMax M1 80K 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, GLM-4.5V or MiniMax M1 80K?
GLM-4.5V is cheaper at $0.60 input / $1.80 output per million tokens (official Z.AI API price). MiniMax M1 80K costs $0.55 input / $2.20 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.90 per million tokens for GLM-4.5V versus $0.963 for MiniMax M1 80K (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.5V has not been scored yet and MiniMax M1 80K has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V and MiniMax M1 80K yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
MiniMax M1 80K has the largest context window at 1,000,000 tokens, against 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, MiniMax M1 80K up to 80,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; MiniMax M1 80K accepts text. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
GLM-4.5V is the newest, released Aug 11, 2025. MiniMax M1 80K came out Jun 17, 2025. Knowledge cutoff: GLM-4.5V 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 Nov 2, 2026.
