Granite-4.0-H-Micro vs Voxtral Mini 3B 2507 vs Sarvam 30B
Too close to call on our weighted score (Granite-4.0-H-Micro 65, Sarvam 30B 65, Voxtral Mini 3B 2507 61). The right pick depends on what you value most.
IBMGranite-4.0-H-Micro
65/100- ECI—
- Price$0.017 / $0.112
- Context131K
Mistral AIVoxtral Mini 3B 2507
61/100- ECI—
- Price$0.04 / $0.04
- Context33K
Sarvam AI
Sarvam 30B
65/100- ECI—
- Price$0.02 / $0.10
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Granite-4.0-H-Micro 65/100, Sarvam 30B 65/100, Voxtral Mini 3B 2507 61/100), 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 2507 and Sarvam 30BVoxtral Mini 3B 2507 $0.04 · Sarvam 30B $0.04 · Granite-4.0-H-Micro $0.041 per 1M tokens (3:1 blend)
- Longest contextGranite-4.0-H-MicroGranite-4.0-H-Micro 131,072 · Sarvam 30B 128,000 · Voxtral Mini 3B 2507 32,768 tokens
- Widest inputsVoxtral Mini 3B 2507Granite-4.0-H-Micro: Text · Voxtral Mini 3B 2507: Text, Audio · Sarvam 30B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Granite-4.0-H-Micro | Voxtral Mini 3B 2507 | Sarvam 30B |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 24 | 0 | 24 |
| Overall | 100% | 65/100 | 61/100 | 65/100 |
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 | Granite-4.0-H-MicroIBM | Voxtral Mini 3B 2507Mistral AI | Sarvam 30BSarvam AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.017 (best) | $0.04 | $0.02 |
| Output | $0.112 | $0.04 (best) | $0.10 |
| Cached input | — | — | — |
| Blended (3:1) | $0.041 | $0.04 (best) | $0.04 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 32,768 tokens | 128,000 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | No | No | Yes · low · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Open |
| API model ID | — | — | sarvam-30b |
| API providers | 1 | 2 (best) | 2 (best) |
| Released | Oct 2, 2025 | Jul 15, 2025 | Feb 18, 2026 |
| 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$0.394
- Voxtral Mini 3B 2507$0.48
- Sarvam 30B$0.40
Which should you choose?
Which is better: Granite-4.0-H-Micro, Voxtral Mini 3B 2507 or Sarvam 30B?
It is close. Our weighted score puts them within a point (Granite-4.0-H-Micro 65/100, Sarvam 30B 65/100, Voxtral Mini 3B 2507 61/100), 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, Voxtral Mini 3B 2507 or Sarvam 30B?
Voxtral Mini 3B 2507 is cheaper at $0.04 input / $0.04 output per million tokens (median across 2 API providers). Sarvam 30B costs $0.02 input / $0.10 output per million tokens (median across 1 API provider); Granite-4.0-H-Micro costs $0.017 input / $0.112 output per million tokens (median across 1 API provider). 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 $0.04 for Sarvam 30B (1× as much) and $0.041 for Granite-4.0-H-Micro (1× 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, Voxtral Mini 3B 2507 has not been scored yet and Sarvam 30B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite-4.0-H-Micro, Voxtral Mini 3B 2507 and Sarvam 30B 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?
Granite-4.0-H-Micro has the largest context window at 131,072 tokens, against 128,000 for Sarvam 30B and 32,768 for Voxtral Mini 3B 2507. Maximum output per response: Granite-4.0-H-Micro up to 131,072, Voxtral Mini 3B 2507 up to 32,768, Sarvam 30B up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Granite-4.0-H-Micro accepts text; Voxtral Mini 3B 2507 accepts text and audio; Sarvam 30B accepts text. Voxtral Mini 3B 2507 handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Sarvam 30B is the newest, released Feb 18, 2026. 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 Oct 4, 2026.
