Sarvam 105B vs Granite-4.0-H-Small
Too close to call on our weighted score (Sarvam 105B 65, Granite-4.0-H-Small 63). The right pick depends on what you value most.
Sarvam AI
Sarvam 105B
65/100- ECI—
- Price$0.047 / $0.186
- Context131K
IBMGranite-4.0-H-Small
63/100- ECI—
- Price$0.064 / $0.265
- Context131K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (Sarvam 105B 65/100, Granite-4.0-H-Small 63/100), so choose by what matters most for your work: Sarvam 105B 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 priceSarvam 105BSarvam 105B $0.082 · Granite-4.0-H-Small $0.114 per 1M tokens (3:1 blend)
- Longest contextAbout the sameSarvam 105B 131,072 · Granite-4.0-H-Small 131,072 tokens
- Widest inputsSame inputsSarvam 105B: Text · Granite-4.0-H-Small: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Sarvam 105B | Granite-4.0-H-Small |
|---|---|---|---|
| Price | 50% | 100 | 95 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 65/100 | 63/100 |
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 | Sarvam 105BSarvam AI | Granite-4.0-H-SmallIBM |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.047 (best) | $0.064 |
| Output | $0.186 (best) | $0.265 |
| Cached input | — | — |
| Blended (3:1) | $0.082 (best) | $0.114 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official watsonx.ai API |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes · low · medium · high | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Open |
| API model ID | sarvam-105b | ibm/granite-4-h-small |
| API providers | 3 (best) | 1 |
| Released | Sep 1, 2025 | Oct 2, 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.
- Sarvam 105B$0.842
- Granite-4.0-H-Small$1.17
Which should you choose?
Which is better: Sarvam 105B or Granite-4.0-H-Small?
It is close. Our weighted score puts them within 3 points (Sarvam 105B 65/100, Granite-4.0-H-Small 63/100), so choose by what matters most for your work: Sarvam 105B 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, Sarvam 105B or Granite-4.0-H-Small?
Sarvam 105B is cheaper at $0.047 input / $0.186 output per million tokens (median across 2 API providers). Granite-4.0-H-Small costs $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). At a typical mix of three input tokens to one output token, that is $0.082 per million tokens for Sarvam 105B versus $0.114 for Granite-4.0-H-Small (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Sarvam 105B has not been scored yet and Granite-4.0-H-Small has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam 105B and Granite-4.0-H-Small 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?
Sarvam 105B and Granite-4.0-H-Small share the same 131,072-token context window. Maximum output per response: Sarvam 105B up to 131,072, Granite-4.0-H-Small up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Sarvam 105B accepts text; Granite-4.0-H-Small accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Granite-4.0-H-Small is the newest, released Oct 2, 2025. Sarvam 105B came out Sep 1, 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.
