GLM-4.7-FlashX vs MiMo-V2.5-Pro vs Step 3.5 Flash
Too close to call on our weighted score (Step 3.5 Flash 62, GLM-4.7-FlashX 61, MiMo-V2.5-Pro 54). 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-V2.5-Pro
54/100- ECI—
- Price$0.435 / $0.87
- Context1.05M
StepFunStep 3.5 Flash
62/100- ECI—
- Price$0.10 / $0.30
- Context256K
Too close to call
It is close. Our weighted score puts them within 1 points (Step 3.5 Flash 62/100, GLM-4.7-FlashX 61/100, MiMo-V2.5-Pro 54/100), so choose by what matters most for your work: Step 3.5 Flash on price and MiMo-V2.5-Pro 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 priceStep 3.5 FlashStep 3.5 Flash $0.15 · GLM-4.7-FlashX $0.152 · MiMo-V2.5-Pro $0.544 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2.5-ProMiMo-V2.5-Pro 1,048,576 · Step 3.5 Flash 256,000 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsSame inputsGLM-4.7-FlashX: Text · MiMo-V2.5-Pro: Text · Step 3.5 Flash: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.7-FlashX | MiMo-V2.5-Pro | Step 3.5 Flash |
|---|---|---|---|---|
| Price | 50% | 89 | 62 | 89 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 32 | 61 | 36 |
| Overall | 100% | 61/100 | 54/100 | 62/100 |
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-V2.5-ProXiaomi | Step 3.5 FlashStepFun |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.07 (best) | $0.435 | $0.10 |
| Output | $0.40 | $0.87 | $0.30 (best) |
| Cached input | $0.01 | $0.0036 (best) | $0.02 |
| Blended (3:1) | $0.152 | $0.544 | $0.15 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Xiaomi API | Official StepFun (Global) API |
| Limits | |||
| Context window | 200,000 tokens | 1,048,576 tokens (best) | 256,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens | 256,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yeslow · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | glm-4.7-flashx | mimo-v2.5-pro | step-3.5-flash |
| API providers | 8 | 20 (best) | 8 |
| Released | Jan 19, 2026 | Apr 22, 2026 | Jan 29, 2026 |
| Knowledge cutoff | Apr 2025 | Dec 2024 | Jan 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-4.7-FlashX$1.50
- MiMo-V2.5-Pro$6.09
- Step 3.5 Flash$1.60
Which should you choose?
Which is better: GLM-4.7-FlashX, MiMo-V2.5-Pro or Step 3.5 Flash?
It is close. Our weighted score puts them within 1 points (Step 3.5 Flash 62/100, GLM-4.7-FlashX 61/100, MiMo-V2.5-Pro 54/100), so choose by what matters most for your work: Step 3.5 Flash on price and MiMo-V2.5-Pro 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, MiMo-V2.5-Pro or Step 3.5 Flash?
Step 3.5 Flash is cheaper at $0.10 input / $0.30 output per million tokens (official StepFun (Global) API price). GLM-4.7-FlashX costs $0.07 input / $0.40 output per million tokens (official Z.AI API price); MiMo-V2.5-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 $0.15 per million tokens for Step 3.5 Flash versus $0.152 for GLM-4.7-FlashX (1× as much) and $0.544 for MiMo-V2.5-Pro (3.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.7-FlashX has not been scored yet, MiMo-V2.5-Pro has not been scored yet and Step 3.5 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-FlashX, MiMo-V2.5-Pro and Step 3.5 Flash 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?
MiMo-V2.5-Pro has the largest context window at 1,048,576 tokens, against 256,000 for Step 3.5 Flash and 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, MiMo-V2.5-Pro up to 131,072, Step 3.5 Flash up to 256,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; MiMo-V2.5-Pro accepts text; Step 3.5 Flash accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
MiMo-V2.5-Pro is the newest, released Apr 22, 2026. Step 3.5 Flash came out Jan 29, 2026; GLM-4.7-FlashX came out Jan 19, 2026. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, MiMo-V2.5-Pro Dec 2024, Step 3.5 Flash Jan 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.
