Claude Haiku 3.5 vs Llama-3.2-11B-Vision-Instruct vs Mistral Large 2.1
Llama-3.2-11B-Vision-Instruct comes out ahead, 64 to 44 and 25 on our weighted score, and it is the cheaper option too.
AnthropicClaude Haiku 3.5
44/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
- Our pick
MetaLlama-3.2-11B-Vision-Instruct
64/100- ECI—
- Price$0.055 / $0.345
- Context128K
Mistral AIMistral Large 2.1
25/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
Llama-3.2-11B-Vision-Instruct is our pick
Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 64/100 against Claude Haiku 3.5 (44) and Mistral Large 2.1 (25). It leads on price. Claude Haiku 3.5 wins 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 priceLlama-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct $0.128 · Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 · Llama-3.2-11B-Vision-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Llama-3.2-11B-Vision-Instruct: Text, Images · Mistral Large 2.1: Text
- Self-hostingLlama-3.2-11B-Vision-Instruct and Mistral Large 2.1Publishes downloadable weights
| Measure | Weight | Claude Haiku 3.5 | Llama-3.2-11B-Vision-Instruct | Mistral Large 2.1 |
|---|---|---|---|---|
| Price | 50% | 38 | 88 | 26 |
| Inputs & features | 30% | 60 | 50 | 25 |
| Context window | 20% | 32 | 24 | 25 |
| Overall | 100% | 44/100 | 64/100 | 25/100 |
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 | Claude Haiku 3.5Anthropic | Llama-3.2-11B-Vision-InstructMeta | Mistral Large 2.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.0 | — | 128.6 (best) |
| ECI rank | #147 of 165 | — | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | — | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | — | 7.8% (best) |
| Price per million tokens | |||
| Input | $0.80 | $0.055 (best) | $2.00 |
| Output | $4.00 | $0.345 (best) | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.60 | $0.128 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 3 providers | Median of 2 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 128,000 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 4,096 tokens | 16,384 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | 4 (best) | 4 (best) | 2 |
| Released | Oct 22, 2024 | Sep 25, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jul 31, 2024 | Dec 2023 | 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.
- Claude Haiku 3.5$16.00
- Llama-3.2-11B-Vision-Instruct$1.24
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Claude Haiku 3.5, Llama-3.2-11B-Vision-Instruct or Mistral Large 2.1?
Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 64/100 against Claude Haiku 3.5 (44) and Mistral Large 2.1 (25). It leads on price. Claude Haiku 3.5 wins 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, Claude Haiku 3.5, Llama-3.2-11B-Vision-Instruct or Mistral Large 2.1?
Llama-3.2-11B-Vision-Instruct is cheaper at $0.055 input / $0.345 output per million tokens (median across 3 API providers). Claude Haiku 3.5 costs $0.80 input / $4.00 output per million tokens (median across 3 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 $0.128 per million tokens for Llama-3.2-11B-Vision-Instruct versus $1.60 for Claude Haiku 3.5 (13× as much) and $3.00 for Mistral Large 2.1 (24× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Claude Haiku 3.5 has an ECI of 127.0, Llama-3.2-11B-Vision-Instruct has not been scored yet and Mistral Large 2.1 has an ECI of 128.6.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Llama-3.2-11B-Vision-Instruct and Mistral Large 2.1 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?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2.1 and 128,000 for Llama-3.2-11B-Vision-Instruct. Maximum output per response: Claude Haiku 3.5 up to 8,192, Llama-3.2-11B-Vision-Instruct up to 4,096, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.2-11B-Vision-Instruct accepts text and images; Mistral Large 2.1 accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.2-11B-Vision-Instruct and Mistral Large 2.1 publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Claude Haiku 3.5 came out Oct 22, 2024; Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Llama-3.2-11B-Vision-Instruct Dec 2023, 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 Nov 2, 2026.
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