Mistral Large 2.1 vs Nemotron VoiceChat
Nemotron VoiceChat comes out ahead, 65 to 26 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 2.1
26/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
- Our pick
NVIDIANemotron VoiceChat
65/100- ECI—
- PriceFree / Free
- Context128K
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Make it a three-way comparison.
Nemotron VoiceChat is our pick
Nemotron VoiceChat is the better all-round choice, scoring 65/100 against Mistral Large 2.1 (26). It leads on price and 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 priceNemotron VoiceChatNemotron VoiceChat Free · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Nemotron VoiceChat 128,000 tokens
- Widest inputsNemotron VoiceChatMistral Large 2.1: Text · Nemotron VoiceChat: Text, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Large 2.1 | Nemotron VoiceChat |
|---|---|---|---|
| Price | 50% | 27 | 100 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 26/100 | 65/100 |
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 | Mistral Large 2.1Mistral AI | Nemotron VoiceChatNVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 128.5 | — |
| ECI rank | #130 of 148 | — |
| GPQA DiamondGraduate-level science questions | 51.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% | — |
| Price per million tokens | ||
| Input | $2.00 | Free (best) |
| Output | $6.00 | Free (best) |
| Cached input | — | — |
| Blended (3:1) | $3.00 | Free (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Nvidia API |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | mistral-large-2411 | nvidia/nemotron-voicechat |
| API providers | 2 (best) | 1 |
| Released | Nov 18, 2024 | Mar 16, 2026 |
| Knowledge cutoff | Nov 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Large 2.1$32.00
- Nemotron VoiceChatFree
Which should you choose?
Which is better: Mistral Large 2.1 or Nemotron VoiceChat?
Nemotron VoiceChat is the better all-round choice, scoring 65/100 against Mistral Large 2.1 (26). It leads on price and 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, Mistral Large 2.1 or Nemotron VoiceChat?
Nemotron VoiceChat is cheaper at Free input / Free output per million tokens (official Nvidia API price). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). Nemotron VoiceChat is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mistral Large 2.1 has an ECI of 128.5 and Nemotron VoiceChat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2.1 and Nemotron VoiceChat 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?
Mistral Large 2.1 has the largest context window at 131,072 tokens, against 128,000 for Nemotron VoiceChat. Maximum output per response: Mistral Large 2.1 up to 16,384, Nemotron VoiceChat up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2.1 accepts text; Nemotron VoiceChat accepts text and audio. Nemotron VoiceChat handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Nemotron VoiceChat is the newest, released Mar 16, 2026. Mistral Large 2.1 came out Nov 18, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024.
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.
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