GLM-4.7-FlashX vs MiMo-V2-Flash
Too close to call on our weighted score (GLM-4.7-FlashX 61, MiMo-V2-Flash 61). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
XiaomiMiMo-V2-Flash
61/100- ECI—
- Price$0.14 / $0.28
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (GLM-4.7-FlashX 61/100, MiMo-V2-Flash 61/100), so choose by what matters most for your work: GLM-4.7-FlashX on price and MiMo-V2-Flash 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-4.7-FlashXGLM-4.7-FlashX $0.152 · MiMo-V2-Flash $0.175 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2-FlashMiMo-V2-Flash 262,144 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsSame inputsGLM-4.7-FlashX: Text · MiMo-V2-Flash: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.7-FlashX | MiMo-V2-Flash |
|---|---|---|---|
| Price | 50% | 89 | 86 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 32 | 37 |
| Overall | 100% | 61/100 | 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 | GLM-4.7-FlashXZ.ai (Zhipu) | MiMo-V2-FlashXiaomi |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.07 (best) | $0.14 |
| Output | $0.40 | $0.28 (best) |
| Cached input | $0.01 | $0.0028 (best) |
| Blended (3:1) | $0.152 (best) | $0.175 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Xiaomi API |
| Limits | ||
| Context window | 200,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 65,536 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 | Open | Open |
| API model ID | glm-4.7-flashx | mimo-v2-flash |
| API providers | 8 (best) | 3 |
| Released | Jan 19, 2026 | Dec 16, 2025 |
| Knowledge cutoff | Apr 2025 | Dec 1, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.7-FlashX$1.50
- MiMo-V2-Flash$1.96
Which should you choose?
Which is better: GLM-4.7-FlashX or MiMo-V2-Flash?
It is close. Our weighted score puts them within a point (GLM-4.7-FlashX 61/100, MiMo-V2-Flash 61/100), so choose by what matters most for your work: GLM-4.7-FlashX on price and MiMo-V2-Flash 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-4.7-FlashX or MiMo-V2-Flash?
GLM-4.7-FlashX is cheaper at $0.07 input / $0.40 output per million tokens (official Z.AI API price). MiMo-V2-Flash costs $0.14 input / $0.28 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 $0.175 for MiMo-V2-Flash (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.7-FlashX has not been scored yet and MiMo-V2-Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-FlashX and MiMo-V2-Flash 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-Flash has the largest context window at 262,144 tokens, against 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, MiMo-V2-Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; MiMo-V2-Flash accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-4.7-FlashX is the newest, released Jan 19, 2026. MiMo-V2-Flash came out Dec 16, 2025. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, MiMo-V2-Flash Dec 1, 2024.
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.
