Ministral 3 14B vs Nemotron Nano 12B v2 VL vs Grok 4.1 Fast
Grok 4.1 Fast comes out ahead, 71 to 63 and 63 on our weighted score, and it is the cheaper option too.
Mistral AIMinistral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
NVIDIANemotron Nano 12B v2 VL
63/100- ECI—
- Price$0.20 / $0.60
- Context128K
- 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 Ministral 3 14B (63) and Nemotron Nano 12B v2 VL (63). It leads on context window. Nemotron Nano 12B v2 VL wins on inputs & features. 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 priceGrok 4.1 FastGrok 4.1 Fast $0.275 · Ministral 3 14B $0.282 · Nemotron Nano 12B v2 VL $0.30 per 1M tokens (3:1 blend)
- Longest contextGrok 4.1 FastGrok 4.1 Fast 2,000,000 · Ministral 3 14B 262,144 · Nemotron Nano 12B v2 VL 128,000 tokens
- Widest inputsNemotron Nano 12B v2 VLMinistral 3 14B: Text, Images · Nemotron Nano 12B v2 VL: Text, Images, Video · Grok 4.1 Fast: Text, Images
- Self-hostingMinistral 3 14B and Nemotron Nano 12B v2 VLPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Ministral 3 14B | Nemotron Nano 12B v2 VL | Grok 4.1 Fast |
|---|---|---|---|---|
| Price | 50% | 76 | 75 | 76 |
| Inputs & features | 30% | 60 | 70 | 60 |
| Context window | 20% | 37 | 24 | 72 |
| Overall | 100% | 63/100 | 63/100 | 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 12B v2 VLNVIDIA | Grok 4.1 FastxAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.268 | $0.20 (best) | $0.20 (best) |
| Output | $0.325 (best) | $0.60 | $0.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.282 | $0.30 | $0.275 (best) |
| 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 | 128,000 tokens | 2,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 128,000 tokens | 30,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | 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/nemotron-nano-12b-v2-vl | — |
| API providers | 2 | 4 (best) | 2 |
| Released | Dec 2, 2025 | Oct 28, 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 12B v2 VL$3.20
- Grok 4.1 Fast$3.00
Which should you choose?
Which is better: Ministral 3 14B, Nemotron Nano 12B v2 VL or Grok 4.1 Fast?
Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Ministral 3 14B (63) and Nemotron Nano 12B v2 VL (63). It leads on context window. Nemotron Nano 12B v2 VL wins on inputs & features. 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 12B v2 VL or Grok 4.1 Fast?
Grok 4.1 Fast is cheaper at $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); Nemotron Nano 12B v2 VL costs $0.20 input / $0.60 output per million tokens (median across 3 API providers; free on Nvidia). At a typical mix of three input tokens to one output token, that is $0.275 per million tokens for Grok 4.1 Fast versus $0.282 for Ministral 3 14B (1× as much) and $0.30 for Nemotron Nano 12B v2 VL (1.1× 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 12B v2 VL 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 12B v2 VL 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 128,000 for Nemotron Nano 12B v2 VL. Maximum output per response: Ministral 3 14B up to 262,144, Nemotron Nano 12B v2 VL up to 128,000, 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 12B v2 VL accepts text, images and video; Grok 4.1 Fast accepts text and images. Nemotron Nano 12B v2 VL handles the widest range of inputs.
Are any of these open source?
Ministral 3 14B and Nemotron Nano 12B v2 VL 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 12B v2 VL came out Oct 28, 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.
