MiMo-V2-Omni vs GLM-4.7-FlashX
MiMo-V2-Omni comes out ahead, 77 to 61 on our weighted score, though GLM-4.7-FlashX is 13% cheaper per token.
- Our pick
XiaomiMiMo-V2-Omni
77/100- ECI—
- Price$0.14 / $0.28
- Context262K
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
Add a model
Make it a three-way comparison.
MiMo-V2-Omni is our pick
MiMo-V2-Omni is the better all-round choice, scoring 77/100 against GLM-4.7-FlashX (61). It leads on inputs & features and context window. GLM-4.7-FlashX wins on price. 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-Omni $0.175 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2-OmniMiMo-V2-Omni 262,144 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsMiMo-V2-OmniMiMo-V2-Omni: Text, Images, PDFs, Audio, Video · GLM-4.7-FlashX: Text
- Self-hostingGLM-4.7-FlashXPublishes downloadable weights
| Measure | Weight | MiMo-V2-Omni | GLM-4.7-FlashX |
|---|---|---|---|
| Price | 50% | 86 | 89 |
| Inputs & features | 30% | 90 | 35 |
| Context window | 20% | 37 | 32 |
| Overall | 100% | 77/100 | 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-OmniXiaomi | GLM-4.7-FlashXZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.14 | $0.07 (best) |
| Output | $0.28 (best) | $0.40 |
| Cached input | $0.0028 (best) | $0.01 |
| Blended (3:1) | $0.175 | $0.152 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Xiaomi API | Official Z.AI API |
| Limits | ||
| Context window | 262,144 tokens (best) | 200,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | mimo-v2-omni | glm-4.7-flashx |
| API providers | 2 | 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-Omni$1.96
- GLM-4.7-FlashX$1.50
Which should you choose?
Which is better: MiMo-V2-Omni or GLM-4.7-FlashX?
MiMo-V2-Omni is the better all-round choice, scoring 77/100 against GLM-4.7-FlashX (61). It leads on inputs & features and context window. GLM-4.7-FlashX wins on price. 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-Omni 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-Omni 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-Omni (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. MiMo-V2-Omni 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-Omni 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-Omni has the largest context window at 262,144 tokens, against 200,000 for GLM-4.7-FlashX. Maximum output per response: MiMo-V2-Omni up to 131,072, GLM-4.7-FlashX up to 131,072 tokens.
Which can read images, PDFs, audio or video?
MiMo-V2-Omni accepts text, images, PDFs, audio and video; GLM-4.7-FlashX accepts text. MiMo-V2-Omni handles the widest range of inputs.
Are any of these open source?
GLM-4.7-FlashX publishes its weights and can be self-hosted; MiMo-V2-Omni is proprietary.
Which is newer?
MiMo-V2-Omni is the newest, released Mar 18, 2026. GLM-4.7-FlashX came out Jan 19, 2026. Knowledge cutoff: MiMo-V2-Omni 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.
