Gemini 2.0 Flash-Lite vs Mistral Large 2.1 vs Nova Lite
Gemini 2.0 Flash-Lite comes out ahead, 82 to 75 and 25 on our weighted score, though Nova Lite is 6% cheaper per token.
- Our pick
GoogleGemini 2.0 Flash-Lite
82/100- ECI—
- Price$0.064 / $0.255
- Context1.05M
Mistral AIMistral Large 2.1
25/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
AmazonNova Lite
75/100- ECI—
- Price$0.06 / $0.24
- Context300K
Gemini 2.0 Flash-Lite is our pick
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Mistral Large 2.1 (25). It leads on inputs & features and 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 priceNova LiteNova Lite $0.105 · Gemini 2.0 Flash-Lite $0.111 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite 1,048,576 · Nova Lite 300,000 · Mistral Large 2.1 131,072 tokens
- Widest inputsGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite: Text, Images, PDFs, Audio, Video · Mistral Large 2.1: Text · Nova Lite: Text, Images, PDFs, Video
- Self-hostingMistral Large 2.1Publishes downloadable weights
| Measure | Weight | Gemini 2.0 Flash-Lite | Mistral Large 2.1 | Nova Lite |
|---|---|---|---|---|
| Price | 50% | 91 | 26 | 92 |
| Inputs & features | 30% | 80 | 25 | 70 |
| Context window | 20% | 61 | 25 | 39 |
| Overall | 100% | 82/100 | 25/100 | 75/100 |
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 | Gemini 2.0 Flash-LiteGoogle | Mistral Large 2.1Mistral AI | Nova LiteAmazon |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 128.6 | — |
| ECI rank | — | #142 of 165 | — |
| GPQA DiamondGraduate-level science questions | — | 51.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% | — |
| Price per million tokens | |||
| Input | $0.064 | $2.00 | $0.06 (best) |
| Output | $0.255 | $6.00 | $0.24 (best) |
| Cached input | — | — | $0.015 |
| Blended (3:1) | $0.111 | $3.00 | $0.105 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Official Amazon Bedrock API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 300,000 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) | 10,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | — | amazon.nova-lite-v1:0 |
| API providers | 3 | 2 | 8 (best) |
| Released | Dec 11, 2024 | Nov 18, 2024 | Dec 3, 2024 |
| Knowledge cutoff | Jun 2024 | Nov 2024 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.0 Flash-Lite$1.15
- Mistral Large 2.1$32.00
- Nova Lite$1.08
Which should you choose?
Which is better: Gemini 2.0 Flash-Lite, Mistral Large 2.1 or Nova Lite?
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Mistral Large 2.1 (25). It leads on inputs & features and 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, Gemini 2.0 Flash-Lite, Mistral Large 2.1 or Nova Lite?
Nova Lite is cheaper at $0.06 input / $0.24 output per million tokens (official Amazon Bedrock API price). Gemini 2.0 Flash-Lite costs $0.064 input / $0.255 output per million tokens (median across 2 API providers); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.105 per million tokens for Nova Lite versus $0.111 for Gemini 2.0 Flash-Lite (1.1× as much) and $3.00 for Mistral Large 2.1 (29× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.0 Flash-Lite has not been scored yet, Mistral Large 2.1 has an ECI of 128.6 and Nova Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.0 Flash-Lite, Mistral Large 2.1 and Nova Lite 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?
Gemini 2.0 Flash-Lite has the largest context window at 1,048,576 tokens, against 300,000 for Nova Lite and 131,072 for Mistral Large 2.1. Maximum output per response: Gemini 2.0 Flash-Lite up to 8,192, Mistral Large 2.1 up to 16,384, Nova Lite up to 10,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash-Lite accepts text, images, PDFs, audio and video; Mistral Large 2.1 accepts text; Nova Lite accepts text, images, PDFs and video. Gemini 2.0 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Mistral Large 2.1 publishes its weights and can be self-hosted; Gemini 2.0 Flash-Lite and Nova Lite is proprietary.
Which is newer?
Gemini 2.0 Flash-Lite is the newest, released Dec 11, 2024. Nova Lite came out Dec 3, 2024; Mistral Large 2.1 came out Nov 18, 2024. Knowledge cutoff: Gemini 2.0 Flash-Lite Jun 2024, Mistral Large 2.1 Nov 2024, Nova Lite Oct 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 Nov 2, 2026.
