Ministral 14B vs Granite-4.0-H-Small
Too close to call on our weighted score (Ministral 14B 63, Granite-4.0-H-Small 61). The right pick depends on what you value most.
Mistral AIMinistral 14B
63/100- ECI—
- Price$0.175 / $0.175
- Context262K
IBMGranite-4.0-H-Small
61/100- 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 (Ministral 14B 63/100, Granite-4.0-H-Small 61/100), so choose by what matters most for your work: Granite-4.0-H-Small on price and Ministral 14B 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 priceGranite-4.0-H-SmallGranite-4.0-H-Small $0.114 · Ministral 14B $0.175 per 1M tokens (3:1 blend)
- Longest contextMinistral 14BMinistral 14B 262,144 · Granite-4.0-H-Small 131,072 tokens
- Widest inputsMinistral 14BMinistral 14B: Text, Images · Granite-4.0-H-Small: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ministral 14B | Granite-4.0-H-Small |
|---|---|---|---|
| Price | 50% | 82 | 91 |
| Inputs & features | 30% | 50 | 35 |
| Context window | 20% | 37 | 25 |
| Overall | 100% | 63/100 | 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 | Ministral 14BMistral AI | Granite-4.0-H-SmallIBM |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.175 | $0.064 (best) |
| Output | $0.175 (best) | $0.265 |
| Cached input | — | — |
| Blended (3:1) | $0.175 | $0.114 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official watsonx.ai API |
| Limits | ||
| Context window | 262,144 tokens (best) | 131,072 tokens |
| Max output | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenApache-2.0 | Open |
| API model ID | — | ibm/granite-4-h-small |
| API providers | 2 (best) | 1 |
| Released | Dec 2, 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.
- Ministral 14B$2.10
- Granite-4.0-H-Small$1.17
Which should you choose?
Which is better: Ministral 14B or Granite-4.0-H-Small?
It is close. Our weighted score puts them within 3 points (Ministral 14B 63/100, Granite-4.0-H-Small 61/100), so choose by what matters most for your work: Granite-4.0-H-Small on price and Ministral 14B 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, Ministral 14B or Granite-4.0-H-Small?
Granite-4.0-H-Small is cheaper at $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). Ministral 14B costs $0.175 input / $0.175 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.114 per million tokens for Granite-4.0-H-Small versus $0.175 for Ministral 14B (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Ministral 14B 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 Ministral 14B 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?
Ministral 14B has the largest context window at 262,144 tokens, against 131,072 for Granite-4.0-H-Small. Maximum output per response: Ministral 14B up to 262,144, Granite-4.0-H-Small up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Ministral 14B accepts text and images; Granite-4.0-H-Small accepts text. Ministral 14B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Ministral 14B is the newest, released Dec 2, 2025. Granite-4.0-H-Small came out Oct 2, 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.
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