Claude Sonnet 3.5 v2 vs Mistral Large 2.1 vs Gemini 2.0 Flash
Gemini 2.0 Flash comes out ahead, 65 to 54 and 42 on our weighted score.
AnthropicClaude Sonnet 3.5 v2
54/100- ECI133.5
- Price$3.00 / $15.00
- Context200K
Mistral AIMistral Large 2.1
42/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
- Our pick
GoogleGemini 2.0 Flash
65/100- ECI134.7
- Price—
- Context1.05M
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 FlashClaude Sonnet 3.5 v2: Text, Images, PDFs · Mistral Large 2.1: Text · Gemini 2.0 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingMistral Large 2.1Publishes downloadable weights
| Measure | Weight | Claude Sonnet 3.5 v2 | Mistral Large 2.1 | Gemini 2.0 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 57 | 51 | 59 |
| Inputs & features | 20% | 60 | 25 | 90 |
| Context window | 13% | 32 | 24 | 61 |
| Overall | 100% | 54/100 | 42/100 | 65/100 |
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 | Claude Sonnet 3.5 v2Anthropic | Mistral Large 2.1Mistral AI | Gemini 2.0 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 133.5 | 128.5 | 134.7 (best) |
| ECI rank | #119 of 148 | #130 of 148 | #116 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 55.3% (best) | 51.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 8.5% (best) | 7.8% | — |
| Price per million tokens | |||
| Input | $3.00 | $2.00 (best) | — |
| Output | $15.00 | $6.00 (best) | — |
| Cached input | — | — | — |
| Blended (3:1) | $6.00 | $3.00 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 1 providers | Official Mistral API | — |
| Limits | |||
| Context window | 200,000 tokens | 131,072 tokens | 1,048,576 tokens (best) |
| 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 | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | mistral-large-2411 | — |
| API providers | 1 | 2 (best) | — |
| Released | Oct 22, 2024 | Nov 18, 2024 | Dec 11, 2024 |
| Knowledge cutoff | Apr 30, 2024 | Nov 2024 | Jun 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Sonnet 3.5 v2$60.00
- Mistral Large 2.1$32.00
- Gemini 2.0 Flash—
Which should you choose?
Which is better: Claude Sonnet 3.5 v2, Mistral Large 2.1 or Gemini 2.0 Flash?
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, Claude Sonnet 3.5 v2, Mistral Large 2.1 or Gemini 2.0 Flash?
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 Claude Sonnet 3.5 v2, Mistral Large 2.1 and Gemini 2.0 Flash 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: Claude Sonnet 3.5 v2 up to 8,192, Mistral Large 2.1 up to 16,384, Gemini 2.0 Flash up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Claude Sonnet 3.5 v2 accepts text, images and PDFs; Mistral Large 2.1 accepts text; Gemini 2.0 Flash accepts text, images, PDFs, audio and video. 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; Claude Sonnet 3.5 v2 and Gemini 2.0 Flash 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: Claude Sonnet 3.5 v2 Apr 30, 2024, Mistral Large 2.1 Nov 2024, Gemini 2.0 Flash Jun 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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