Ministral 3 14B vs Nemotron Nano 9B v2 vs Grok 4.1 Fast
Grok 4.1 Fast comes out ahead, 71 to 64 and 63 on our weighted score, though Nemotron Nano 9B v2 is 2.7× cheaper per token.
Mistral AIMinistral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
NVIDIANemotron Nano 9B v2
64/100- ECI—
- Price$0.06 / $0.23
- Context131K
- Our pick
xAIGrok 4.1 Fast
71/100- ECI—
- Price$0.20 / $0.50
- Context2M
Grok 4.1 Fast is our pick
Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Nemotron Nano 9B v2 (64) and Ministral 3 14B (63). It leads on context window. Nemotron Nano 9B v2 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 priceNemotron Nano 9B v2Nemotron Nano 9B v2 $0.102 · 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 · Nemotron Nano 9B v2 131,072 tokens
- Widest inputsMinistral 3 14B and Grok 4.1 FastMinistral 3 14B: Text, Images · Nemotron Nano 9B v2: Text · Grok 4.1 Fast: Text, Images
- Self-hostingMinistral 3 14B and Nemotron Nano 9B v2Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Ministral 3 14B | Nemotron Nano 9B v2 | Grok 4.1 Fast |
|---|---|---|---|---|
| Price | 50% | 76 | 97 | 76 |
| Inputs & features | 30% | 60 | 35 | 60 |
| Context window | 20% | 37 | 24 | 72 |
| Overall | 100% | 63/100 | 64/100 | 71/100 |
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 3 14BMistral AI | Nemotron Nano 9B v2NVIDIA | Grok 4.1 FastxAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.268 | $0.06 (best) | $0.20 |
| Output | $0.325 | $0.23 (best) | $0.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.282 | $0.102 (best) | $0.275 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 3 providers | Median of 2 providers |
| Limits | |||
| Context window | 262,144 tokens | 131,072 tokens | 2,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 131,072 tokens | 30,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Proprietary |
| API model ID | — | nvidia/nvidia-nemotron-nano-9b-v2 | — |
| API providers | 2 | 4 (best) | 2 |
| Released | Dec 2, 2025 | Aug 18, 2025 | Nov 19, 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 3 14B$3.33
- Nemotron Nano 9B v2$1.06
- Grok 4.1 Fast$3.00
Which should you choose?
Which is better: Ministral 3 14B, Nemotron Nano 9B v2 or Grok 4.1 Fast?
Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Nemotron Nano 9B v2 (64) and Ministral 3 14B (63). It leads on context window. Nemotron Nano 9B v2 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, Ministral 3 14B, Nemotron Nano 9B v2 or Grok 4.1 Fast?
Nemotron Nano 9B v2 is cheaper at $0.06 input / $0.23 output per million tokens (median across 3 API providers; free on Nvidia). 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 $0.102 per million tokens for Nemotron Nano 9B v2 versus $0.275 for Grok 4.1 Fast (2.7× as much) and $0.282 for Ministral 3 14B (2.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Ministral 3 14B has not been scored yet, Nemotron Nano 9B v2 has not been scored yet and Grok 4.1 Fast has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 3 14B, Nemotron Nano 9B v2 and Grok 4.1 Fast 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 Nemotron Nano 9B v2. Maximum output per response: Ministral 3 14B up to 262,144, Nemotron Nano 9B v2 up to 131,072, Grok 4.1 Fast up to 30,000 tokens.
Which can read images, PDFs, audio or video?
Ministral 3 14B accepts text and images; Nemotron Nano 9B v2 accepts text; Grok 4.1 Fast accepts text and images. Ministral 3 14B handles the widest range of inputs.
Are any of these open source?
Ministral 3 14B and Nemotron Nano 9B v2 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; Nemotron Nano 9B v2 came out Aug 18, 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.
