Nemotron Nano 12B v2 VL vs Ministral 3 3B vs Grok 4.1 Fast
Ministral 3 3B comes out ahead, 74 to 71 and 63 on our weighted score, and it is the cheaper option too.
NVIDIANemotron Nano 12B v2 VL
63/100- ECI—
- Price$0.20 / $0.60
- Context128K
- Our pick
Mistral AIMinistral 3 3B
74/100- ECI—
- Price$0.10 / $0.10
- Context262K
xAIGrok 4.1 Fast
71/100- ECI—
- Price$0.20 / $0.50
- Context2M
Ministral 3 3B is our pick
Ministral 3 3B is the better all-round choice, scoring 74/100 against Grok 4.1 Fast (71) and Nemotron Nano 12B v2 VL (63). It leads on price. Nemotron Nano 12B v2 VL wins on inputs & features. Grok 4.1 Fast wins on context window. 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 priceMinistral 3 3BMinistral 3 3B $0.10 · Grok 4.1 Fast $0.275 · 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 3B 262,144 · Nemotron Nano 12B v2 VL 128,000 tokens
- Widest inputsNemotron Nano 12B v2 VLNemotron Nano 12B v2 VL: Text, Images, Video · Ministral 3 3B: Text, Images · Grok 4.1 Fast: Text, Images
- Self-hostingNemotron Nano 12B v2 VL and Ministral 3 3BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Nemotron Nano 12B v2 VL | Ministral 3 3B | Grok 4.1 Fast |
|---|---|---|---|---|
| Price | 50% | 75 | 97 | 76 |
| Inputs & features | 30% | 70 | 60 | 60 |
| Context window | 20% | 24 | 37 | 72 |
| Overall | 100% | 63/100 | 74/100 | 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 | Nemotron Nano 12B v2 VLNVIDIA | Ministral 3 3BMistral AI | Grok 4.1 FastxAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.10 (best) | $0.20 |
| Output | $0.60 | $0.10 (best) | $0.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.30 | $0.10 (best) | $0.275 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 1 providers | Median of 2 providers |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens | 2,000,000 tokens (best) |
| Max output | 128,000 tokens | 262,144 tokens (best) | 30,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | nvidia/nemotron-nano-12b-v2-vl | — | — |
| API providers | 4 (best) | 1 | 2 |
| Released | Oct 28, 2025 | Dec 2, 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.
- Nemotron Nano 12B v2 VL$3.20
- Ministral 3 3B$1.20
- Grok 4.1 Fast$3.00
Which should you choose?
Which is better: Nemotron Nano 12B v2 VL, Ministral 3 3B or Grok 4.1 Fast?
Ministral 3 3B is the better all-round choice, scoring 74/100 against Grok 4.1 Fast (71) and Nemotron Nano 12B v2 VL (63). It leads on price. Nemotron Nano 12B v2 VL wins on inputs & features. Grok 4.1 Fast wins on context window. 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, Nemotron Nano 12B v2 VL, Ministral 3 3B or Grok 4.1 Fast?
Ministral 3 3B is cheaper at $0.10 input / $0.10 output per million tokens (median across 1 API provider). Grok 4.1 Fast costs $0.20 input / $0.50 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 $0.10 per million tokens for Ministral 3 3B versus $0.275 for Grok 4.1 Fast (2.8× as much) and $0.30 for Nemotron Nano 12B v2 VL (3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Nemotron Nano 12B v2 VL has not been scored yet, Ministral 3 3B 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 Nemotron Nano 12B v2 VL, Ministral 3 3B 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 3B and 128,000 for Nemotron Nano 12B v2 VL. Maximum output per response: Nemotron Nano 12B v2 VL up to 128,000, Ministral 3 3B up to 262,144, Grok 4.1 Fast up to 30,000 tokens.
Which can read images, PDFs, audio or video?
Nemotron Nano 12B v2 VL accepts text, images and video; Ministral 3 3B accepts text and images; 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?
Nemotron Nano 12B v2 VL and Ministral 3 3B publishes its weights (Apache 2.0) and can be self-hosted; Grok 4.1 Fast is proprietary.
Which is newer?
Ministral 3 3B 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.
