Granite-4.0-H-Small vs Grok 4.1 Fast vs Ministral 3 14B
Grok 4.1 Fast comes out ahead, 71 to 63 and 63 on our weighted score, though Granite-4.0-H-Small is 2.4× cheaper per token.
IBMGranite-4.0-H-Small
63/100- ECI—
- Price$0.064 / $0.265
- Context131K
- Our pick
xAIGrok 4.1 Fast
71/100- ECI—
- Price$0.20 / $0.50
- Context2M
Mistral AIMinistral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
Grok 4.1 Fast is our pick
Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Ministral 3 14B (63) and Granite-4.0-H-Small (63). It leads on context window. Granite-4.0-H-Small wins 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 priceGranite-4.0-H-SmallGranite-4.0-H-Small $0.114 · Grok 4.1 Fast $0.275 · Ministral 3 14B $0.282 per 1M tokens (3:1 blend)
- Longest contextGrok 4.1 FastGrok 4.1 Fast 2,000,000 · Ministral 3 14B 262,144 · Granite-4.0-H-Small 131,072 tokens
- Widest inputsGrok 4.1 Fast and Ministral 3 14BGranite-4.0-H-Small: Text · Grok 4.1 Fast: Text, Images · Ministral 3 14B: Text, Images
- Self-hostingGranite-4.0-H-Small and Ministral 3 14BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Granite-4.0-H-Small | Grok 4.1 Fast | Ministral 3 14B |
|---|---|---|---|---|
| Price | 50% | 95 | 76 | 76 |
| Inputs & features | 30% | 35 | 60 | 60 |
| Context window | 20% | 24 | 72 | 37 |
| Overall | 100% | 63/100 | 71/100 | 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 | Granite-4.0-H-SmallIBM | Grok 4.1 FastxAI | Ministral 3 14BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.064 (best) | $0.20 | $0.268 |
| Output | $0.265 (best) | $0.50 | $0.325 |
| Cached input | — | — | — |
| Blended (3:1) | $0.114 (best) | $0.275 | $0.282 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official watsonx.ai API | Median of 2 providers | Median of 2 providers |
| Limits | |||
| Context window | 131,072 tokens | 2,000,000 tokens (best) | 262,144 tokens |
| Max output | 131,072 tokens | 30,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | OpenApache 2.0 |
| API model ID | ibm/granite-4-h-small | — | — |
| API providers | 1 | 2 (best) | 2 (best) |
| Released | Oct 2, 2025 | Nov 19, 2025 | Dec 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.
- Granite-4.0-H-Small$1.17
- Grok 4.1 Fast$3.00
- Ministral 3 14B$3.33
Which should you choose?
Which is better: Granite-4.0-H-Small, Grok 4.1 Fast or Ministral 3 14B?
Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Ministral 3 14B (63) and Granite-4.0-H-Small (63). It leads on context window. Granite-4.0-H-Small wins 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, Granite-4.0-H-Small, Grok 4.1 Fast or Ministral 3 14B?
Granite-4.0-H-Small is cheaper at $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). Grok 4.1 Fast costs $0.20 input / $0.50 output per million tokens (median across 2 API providers); Ministral 3 14B costs $0.268 input / $0.325 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 $0.275 for Grok 4.1 Fast (2.4× as much) and $0.282 for Ministral 3 14B (2.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Granite-4.0-H-Small has not been scored yet, Grok 4.1 Fast has not been scored yet and Ministral 3 14B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite-4.0-H-Small, Grok 4.1 Fast and Ministral 3 14B 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?
Grok 4.1 Fast has the largest context window at 2,000,000 tokens, against 262,144 for Ministral 3 14B and 131,072 for Granite-4.0-H-Small. Maximum output per response: Granite-4.0-H-Small up to 131,072, Grok 4.1 Fast up to 30,000, Ministral 3 14B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Granite-4.0-H-Small accepts text; Grok 4.1 Fast accepts text and images; Ministral 3 14B accepts text and images. Grok 4.1 Fast handles the widest range of inputs.
Are any of these open source?
Granite-4.0-H-Small and Ministral 3 14B publishes its weights (Apache 2.0) and can be self-hosted; Grok 4.1 Fast is proprietary.
Which is newer?
Ministral 3 14B is the newest, released Dec 2, 2025. Grok 4.1 Fast came out Nov 19, 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 Oct 4, 2026.
