GLM-4.6V vs Phi-4-mini
Too close to call on our weighted score (GLM-4.6V 59, Phi-4-mini 58). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.6V
59/100- ECI—
- Price$0.30 / $0.90
- Context128K
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
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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-4.6V 59/100, Phi-4-mini 58/100), so choose by what matters most for your work: Phi-4-mini 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 pricePhi-4-miniPhi-4-mini $0.131 · GLM-4.6V $0.45 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGLM-4.6V 128,000 · Phi-4-mini 128,000 tokens
- Widest inputsGLM-4.6VGLM-4.6V: Text, Images, Video · Phi-4-mini: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.6V | Phi-4-mini |
|---|---|---|---|
| Price | 50% | 66 | 92 |
| Inputs & features | 30% | 70 | 25 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 59/100 | 58/100 |
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-4.6VZ.ai (Zhipu) | Phi-4-miniMicrosoft |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.30 | $0.075 (best) |
| Output | $0.90 | $0.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.45 | $0.131 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Azure API |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 32,768 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-4.6v | phi-4-mini |
| API providers | 10 (best) | 1 |
| Released | Dec 8, 2025 | Dec 11, 2024 |
| Knowledge cutoff | Apr 2025 | Oct 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.6V$4.80
- Phi-4-mini$1.35
Which should you choose?
Which is better: GLM-4.6V or Phi-4-mini?
It is close. Our weighted score puts them within a point (GLM-4.6V 59/100, Phi-4-mini 58/100), so choose by what matters most for your work: Phi-4-mini 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, GLM-4.6V or Phi-4-mini?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). GLM-4.6V costs $0.30 input / $0.90 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $0.45 for GLM-4.6V (3.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.6V has not been scored yet and Phi-4-mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6V and Phi-4-mini 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?
GLM-4.6V and Phi-4-mini share the same 128,000-token context window. Maximum output per response: GLM-4.6V up to 32,768, Phi-4-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6V accepts text, images and video; Phi-4-mini accepts text. GLM-4.6V handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-4.6V is the newest, released Dec 8, 2025. Phi-4-mini came out Dec 11, 2024. Knowledge cutoff: GLM-4.6V Apr 2025, Phi-4-mini Oct 2023.
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.
