Granite-4.0-H-Micro vs AutoGLM Phone 9B Multilingual vs Voxtral Mini 3B 2507
Too close to call on our weighted score (Granite-4.0-H-Micro 62, Voxtral Mini 3B 2507 61, AutoGLM Phone 9B Multilingual 60). The right pick depends on what you value most.
IBM
Granite-4.0-H-Micro
62/100- ECI—
- Price$0.018 / $0.115
- Context131K
Z.ai (Zhipu)
AutoGLM Phone 9B Multilingual
60/100- ECI—
- Price$0.035 / $0.138
- Context66K
Mistral AI
Voxtral Mini 3B 2507
61/100- ECI—
- Price$0.04 / $0.04
- Context33K
Too close to call
It is close. Our weighted score puts them within 2 points (Granite-4.0-H-Micro 62/100, Voxtral Mini 3B 2507 61/100, AutoGLM Phone 9B Multilingual 60/100), so choose by what matters most for your work: Voxtral Mini 3B 2507 on price and Granite-4.0-H-Micro 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 priceVoxtral Mini 3B 2507Voxtral Mini 3B 2507 $0.04 · Granite-4.0-H-Micro $0.042 · AutoGLM Phone 9B Multilingual $0.061 per 1M tokens (3:1 blend)
- Longest contextGranite-4.0-H-MicroGranite-4.0-H-Micro 131,072 · AutoGLM Phone 9B Multilingual 65,536 · Voxtral Mini 3B 2507 32,768 tokens
- Widest inputsAutoGLM Phone 9B Multilingual and Voxtral Mini 3B 2507Granite-4.0-H-Micro: Text · AutoGLM Phone 9B Multilingual: Text, Images · Voxtral Mini 3B 2507: Text, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Granite-4.0-H-Micro | AutoGLM Phone 9B Multilingual | Voxtral Mini 3B 2507 |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 25 | 25 | 35 |
| Context window | 20% | 25 | 12 | 0 |
| Overall | 100% | 62/100 | 60/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.018 (best) | $0.035 | $0.04 |
| Output | $0.115 | $0.138 | $0.04 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.042 | $0.061 | $0.04 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Median of 2 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 65,536 tokens | 32,768 tokens |
| Max output | 131,072 tokens (best) | 65,536 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenMIT | OpenApache 2.0 |
| API model ID | — | — | — |
| API providers | 2 | 2 | 3 (best) |
| Released | Oct 2, 2025 | Dec 10, 2025 | Jul 15, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Granite-4.0-H-Micro$0.405
AutoGLM Phone 9B Multilingual$0.626
Voxtral Mini 3B 2507$0.48
Which should you choose?
Which is better: Granite-4.0-H-Micro, AutoGLM Phone 9B Multilingual or Voxtral Mini 3B 2507?
It is close. Our weighted score puts them within 2 points (Granite-4.0-H-Micro 62/100, Voxtral Mini 3B 2507 61/100, AutoGLM Phone 9B Multilingual 60/100), so choose by what matters most for your work: Voxtral Mini 3B 2507 on price and Granite-4.0-H-Micro 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, Granite-4.0-H-Micro, AutoGLM Phone 9B Multilingual or Voxtral Mini 3B 2507?
Voxtral Mini 3B 2507 is cheaper at $0.04 input / $0.04 output per million tokens (median across 2 API providers). Granite-4.0-H-Micro costs $0.018 input / $0.115 output per million tokens (median across 2 API providers); AutoGLM Phone 9B Multilingual costs $0.035 input / $0.138 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.04 per million tokens for Voxtral Mini 3B 2507 versus $0.042 for Granite-4.0-H-Micro (1× as much) and $0.061 for AutoGLM Phone 9B Multilingual (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Granite-4.0-H-Micro has not been scored yet, AutoGLM Phone 9B Multilingual has not been scored yet and Voxtral Mini 3B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite-4.0-H-Micro, AutoGLM Phone 9B Multilingual and Voxtral Mini 3B 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that AutoGLM Phone 9B Multilingual does not support tool calling, which most coding agents need.
Which has the bigger context window?
Granite-4.0-H-Micro has the largest context window at 131,072 tokens, against 65,536 for AutoGLM Phone 9B Multilingual and 32,768 for Voxtral Mini 3B 2507. Maximum output per response: Granite-4.0-H-Micro up to 131,072, AutoGLM Phone 9B Multilingual up to 65,536, Voxtral Mini 3B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Granite-4.0-H-Micro accepts text; AutoGLM Phone 9B Multilingual accepts text and images; Voxtral Mini 3B 2507 accepts text and audio. AutoGLM Phone 9B Multilingual handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (MIT and Apache 2.0), so you can self-host them.
Which is newer?
AutoGLM Phone 9B Multilingual is the newest, released Dec 10, 2025. Granite-4.0-H-Micro came out Oct 2, 2025; Voxtral Mini 3B 2507 came out Jul 15, 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 Nov 2, 2026.