MiMo-V2-Pro vs GLM-4.7-FlashX
GLM-4.7-FlashX comes out ahead, 61 to 54 on our weighted score, and it is the cheaper option too.
XiaomiMiMo-V2-Pro
54/100- ECI—
- Price$0.435 / $0.87
- Context1.05M
- Our pick
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
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Make it a three-way comparison.
GLM-4.7-FlashX is our pick
GLM-4.7-FlashX is the better all-round choice, scoring 61/100 against MiMo-V2-Pro (54). It leads on price. MiMo-V2-Pro 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-4.7-FlashXGLM-4.7-FlashX $0.152 · MiMo-V2-Pro $0.544 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2-ProMiMo-V2-Pro 1,048,576 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsSame inputsMiMo-V2-Pro: Text · GLM-4.7-FlashX: Text
- Self-hostingGLM-4.7-FlashXPublishes downloadable weights
| Measure | Weight | MiMo-V2-Pro | GLM-4.7-FlashX |
|---|---|---|---|
| Price | 50% | 62 | 89 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 61 | 32 |
| Overall | 100% | 54/100 | 61/100 |
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 | MiMo-V2-ProXiaomi | GLM-4.7-FlashXZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.435 | $0.07 (best) |
| Output | $0.87 | $0.40 (best) |
| Cached input | $0.0036 (best) | $0.01 |
| Blended (3:1) | $0.544 | $0.152 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Xiaomi API | Official Z.AI API |
| Limits | ||
| Context window | 1,048,576 tokens (best) | 200,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | mimo-v2-pro | glm-4.7-flashx |
| API providers | 4 | 8 (best) |
| Released | Mar 18, 2026 | Jan 19, 2026 |
| Knowledge cutoff | Dec 2024 | 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.
- MiMo-V2-Pro$6.09
- GLM-4.7-FlashX$1.50
Which should you choose?
Which is better: MiMo-V2-Pro or GLM-4.7-FlashX?
GLM-4.7-FlashX is the better all-round choice, scoring 61/100 against MiMo-V2-Pro (54). It leads on price. MiMo-V2-Pro 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, MiMo-V2-Pro or GLM-4.7-FlashX?
GLM-4.7-FlashX is cheaper at $0.07 input / $0.40 output per million tokens (official Z.AI API price). MiMo-V2-Pro costs $0.435 input / $0.87 output per million tokens (official Xiaomi API price). At a typical mix of three input tokens to one output token, that is $0.152 per million tokens for GLM-4.7-FlashX versus $0.544 for MiMo-V2-Pro (3.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. MiMo-V2-Pro has not been scored yet and GLM-4.7-FlashX has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiMo-V2-Pro and GLM-4.7-FlashX 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?
MiMo-V2-Pro has the largest context window at 1,048,576 tokens, against 200,000 for GLM-4.7-FlashX. Maximum output per response: MiMo-V2-Pro up to 131,072, GLM-4.7-FlashX up to 131,072 tokens.
Which can read images, PDFs, audio or video?
MiMo-V2-Pro accepts text; GLM-4.7-FlashX accepts text. They handle the same number of input types.
Are any of these open source?
GLM-4.7-FlashX publishes its weights and can be self-hosted; MiMo-V2-Pro is proprietary.
Which is newer?
MiMo-V2-Pro is the newest, released Mar 18, 2026. GLM-4.7-FlashX came out Jan 19, 2026. Knowledge cutoff: MiMo-V2-Pro Dec 2024, GLM-4.7-FlashX 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.
