Gemini 2.0 Flash vs Mistral Large 2.1 vs Claude Sonnet 3.5 v2
Gemini 2.0 Flash comes out ahead, 65 to 54 and 42 on our weighted score.
- Our pick
GoogleGemini 2.0 Flash
65/100- ECI134.7
- Price—
- Context1.05M
Mistral AIMistral Large 2.1
42/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
AnthropicClaude Sonnet 3.5 v2
54/100- ECI133.5
- Price$3.00 / $15.00
- Context200K
Gemini 2.0 Flash is our pick
Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and Mistral Large 2.1 (42). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityGemini 2.0 FlashCapabilities Index (ECI): Gemini 2.0 Flash 134.7 · Claude Sonnet 3.5 v2 133.5 · Mistral Large 2.1 128.5
- Lowest priceMistral Large 2.1Mistral Large 2.1 $3.00 · Claude Sonnet 3.5 v2 $6.00 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
- Longest contextGemini 2.0 FlashGemini 2.0 Flash 1,048,576 · Claude Sonnet 3.5 v2 200,000 · Mistral Large 2.1 131,072 tokens
- Widest inputsGemini 2.0 FlashGemini 2.0 Flash: Text, Images, PDFs, Audio, Video · Mistral Large 2.1: Text · Claude Sonnet 3.5 v2: Text, Images, PDFs
- Self-hostingMistral Large 2.1Publishes downloadable weights
| Measure | Weight | Gemini 2.0 Flash | Mistral Large 2.1 | Claude Sonnet 3.5 v2 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 59 | 51 | 57 |
| Inputs & features | 20% | 90 | 25 | 60 |
| Context window | 13% | 61 | 24 | 32 |
| Overall | 100% | 65/100 | 42/100 | 54/100 |
Left out because at least one model lacks the data: price. 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 FlashGoogle | Mistral Large 2.1Mistral AI | Claude Sonnet 3.5 v2Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 134.7 (best) | 128.5 | 133.5 |
| ECI rank | #116 of 148 (best) | #130 of 148 | #119 of 148 |
| GPQA DiamondGraduate-level science questions | — | 51.3% | 55.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% | 8.5% (best) |
| Price per million tokens | |||
| Input | — | $2.00 (best) | $3.00 |
| Output | — | $6.00 (best) | $15.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.00 (best) | $6.00 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Mistral API | Median of 1 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 200,000 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | mistral-large-2411 | — |
| API providers | — | 2 (best) | 1 |
| Released | Dec 11, 2024 | Nov 18, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Jun 2024 | Nov 2024 | Apr 30, 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—
- Mistral Large 2.1$32.00
- Claude Sonnet 3.5 v2$60.00
Which should you choose?
Which is better: Gemini 2.0 Flash, Mistral Large 2.1 or Claude Sonnet 3.5 v2?
Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and Mistral Large 2.1 (42). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemini 2.0 Flash, Mistral Large 2.1 or Claude Sonnet 3.5 v2?
Mistral Large 2.1 is cheaper at $2.00 input / $6.00 output per million tokens (official Mistral API price). Claude Sonnet 3.5 v2 costs $3.00 input / $15.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Large 2.1 versus $6.00 for Claude Sonnet 3.5 v2 (2× as much). Gemini 2.0 Flash has no published per-token price.
Which scores higher on benchmarks?
Gemini 2.0 Flash scores higher on the Capabilities Index (ECI): Gemini 2.0 Flash 134.7 (#116 of 148), Claude Sonnet 3.5 v2 133.5 (#119 of 148) and Mistral Large 2.1 128.5 (#130 of 148). The confidence ranges of the top two overlap (124.3–136.7 vs 129.2–137.5), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.0 Flash, Mistral Large 2.1 and Claude Sonnet 3.5 v2 yet, so there is no like-for-like coding score. On overall capability, Gemini 2.0 Flash leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.0 Flash has the largest context window at 1,048,576 tokens, against 200,000 for Claude Sonnet 3.5 v2 and 131,072 for Mistral Large 2.1. Maximum output per response: Gemini 2.0 Flash up to 8,192, Mistral Large 2.1 up to 16,384, Claude Sonnet 3.5 v2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash accepts text, images, PDFs, audio and video; Mistral Large 2.1 accepts text; Claude Sonnet 3.5 v2 accepts text, images and PDFs. Gemini 2.0 Flash 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 and Claude Sonnet 3.5 v2 is proprietary.
Which is newer?
Gemini 2.0 Flash is the newest, released Dec 11, 2024. Mistral Large 2.1 came out Nov 18, 2024; Claude Sonnet 3.5 v2 came out Oct 22, 2024. Knowledge cutoff: Gemini 2.0 Flash Jun 2024, Mistral Large 2.1 Nov 2024, Claude Sonnet 3.5 v2 Apr 30, 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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