Mistral Large 3 vs Nova 2 Lite vs Qwen Flash
Qwen Flash comes out ahead, 68 to 62 and 50 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
AmazonNova 2 Lite
62/100- ECI—
- Price$0.33 / $2.75
- Context1M
- Our pick
Alibaba (Qwen)Qwen Flash
68/100- ECI—
- Price$0.05 / $0.40
- Context1M
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 68/100 against Nova 2 Lite (62) and Mistral Large 3 (50). It leads on price. Nova 2 Lite 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 priceQwen FlashQwen Flash $0.138 · Mistral Large 3 $0.75 · Nova 2 Lite $0.935 per 1M tokens (3:1 blend)
- Longest contextNova 2 Lite and Qwen FlashNova 2 Lite 1,000,000 · Qwen Flash 1,000,000 · Mistral Large 3 262,144 tokens
- Widest inputsNova 2 LiteMistral Large 3: Text, Images · Nova 2 Lite: Text, Images, PDFs, Video · Qwen Flash: Text
- Self-hostingMistral Large 3Publishes downloadable weights
| Measure | Weight | Mistral Large 3 | Nova 2 Lite | Qwen Flash |
|---|---|---|---|---|
| Price | 50% | 56 | 51 | 91 |
| Inputs & features | 30% | 50 | 80 | 35 |
| Context window | 20% | 37 | 60 | 60 |
| Overall | 100% | 50/100 | 62/100 | 68/100 |
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 3Mistral AI | Nova 2 LiteAmazon | Qwen FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.33 | $0.05 (best) |
| Output | $1.50 | $2.75 | $0.40 (best) |
| Cached input | $0.05 (best) | $0.083 | — |
| Blended (3:1) | $0.75 | $0.935 | $0.138 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Amazon Bedrock API | Official Alibaba API |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 1,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 65,536 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | mistral-large-2512 | amazon.nova-2-lite-v1:0 | qwen-flash |
| API providers | 13 (best) | 2 | 6 |
| Released | Dec 2, 2025 | Dec 2, 2025 | Jul 28, 2025 |
| Knowledge cutoff | Nov 2024 | Oct 2025 | Apr 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 3$8.00
- Nova 2 Lite$8.80
- Qwen Flash$1.30
Which should you choose?
Which is better: Mistral Large 3, Nova 2 Lite or Qwen Flash?
Qwen Flash is the better all-round choice, scoring 68/100 against Nova 2 Lite (62) and Mistral Large 3 (50). It leads on price. Nova 2 Lite 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, Mistral Large 3, Nova 2 Lite or Qwen Flash?
Qwen Flash is cheaper at $0.05 input / $0.40 output per million tokens (official Alibaba API price). Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price); Nova 2 Lite costs $0.33 input / $2.75 output per million tokens (official Amazon Bedrock API price). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for Qwen Flash versus $0.75 for Mistral Large 3 (5.5× as much) and $0.935 for Nova 2 Lite (6.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Large 3 has not been scored yet, Nova 2 Lite has not been scored yet and Qwen Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 3, Nova 2 Lite and Qwen Flash 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?
Nova 2 Lite and Qwen Flash have the largest context windows (1,000,000 and 1,000,000 tokens), against 262,144 for Mistral Large 3. Maximum output per response: Mistral Large 3 up to 262,144, Nova 2 Lite up to 65,536, Qwen Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 3 accepts text and images; Nova 2 Lite accepts text, images, PDFs and video; Qwen Flash accepts text. Nova 2 Lite handles the widest range of inputs.
Are any of these open source?
Mistral Large 3 publishes its weights and can be self-hosted; Nova 2 Lite and Qwen Flash is proprietary.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. Nova 2 Lite came out Dec 2, 2025; Qwen Flash came out Jul 28, 2025. Knowledge cutoff: Mistral Large 3 Nov 2024, Nova 2 Lite Oct 2025, Qwen Flash Apr 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.
