Llama-3.2-90B-Vision-Instruct vs Mistral Large 2.1 vs Claude Haiku 3.5
Claude Haiku 3.5 comes out ahead, 48 to 44 and 42 on our weighted score, and it is the cheaper option too.
MetaLlama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Mistral AIMistral Large 2.1
42/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
- Our pick
AnthropicClaude Haiku 3.5
48/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 48/100 against Llama-3.2-90B-Vision-Instruct (44) and Mistral Large 2.1 (42). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Claude Haiku 3.5 127.0 · Llama-3.2-90B-Vision-Instruct 125.5
- Lowest priceClaude Haiku 3.5Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 · Llama-3.2-90B-Vision-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Llama-3.2-90B-Vision-Instruct: Text, Images · Mistral Large 2.1: Text · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingLlama-3.2-90B-Vision-Instruct and Mistral Large 2.1Publishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Mistral Large 2.1 | Claude Haiku 3.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 46 | 50 | 48 |
| Inputs & features | 20% | 50 | 25 | 60 |
| Context window | 13% | 24 | 25 | 32 |
| Overall | 100% | 44/100 | 42/100 | 48/100 |
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 | Llama-3.2-90B-Vision-InstructMeta | Mistral Large 2.1Mistral AI | Claude Haiku 3.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 125.5 | 128.6 (best) | 127.0 |
| ECI rank | #150 of 165 | #142 of 165 (best) | #147 of 165 |
| GPQA DiamondGraduate-level science questions | 41.0% | 51.3% (best) | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% | 7.8% (best) | 4.3% |
| Price per million tokens | |||
| Input | — | $2.00 | $0.80 (best) |
| Output | — | $6.00 | $4.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.00 | $1.60 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 2 providers | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 200,000 tokens (best) |
| Max output | 4,096 tokens | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 2 | 4 (best) |
| Released | Sep 25, 2024 | Nov 18, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Dec 2023 | Nov 2024 | Jul 31, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.2-90B-Vision-Instruct—
- Mistral Large 2.1$32.00
- Claude Haiku 3.5$16.00
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct, Mistral Large 2.1 or Claude Haiku 3.5?
Claude Haiku 3.5 is the better all-round choice, scoring 48/100 against Llama-3.2-90B-Vision-Instruct (44) and Mistral Large 2.1 (42). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Llama-3.2-90B-Vision-Instruct, Mistral Large 2.1 or Claude Haiku 3.5?
Claude Haiku 3.5 is cheaper at $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 $1.60 per million tokens for Claude Haiku 3.5 versus $3.00 for Mistral Large 2.1 (1.9× as much). Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165), Claude Haiku 3.5 127.0 (#147 of 165) and Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 121.4–129.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Llama-3.2-90B-Vision-Instruct 41.0%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Claude Haiku 3.5 4.3%, Llama-3.2-90B-Vision-Instruct 2.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct, Mistral Large 2.1 and Claude Haiku 3.5 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 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?
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-3.2-90B-Vision-Instruct. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Mistral Large 2.1 up to 16,384, Claude Haiku 3.5 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-90B-Vision-Instruct accepts text and images; Mistral Large 2.1 accepts text; Claude Haiku 3.5 accepts text, images and PDFs. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.2-90B-Vision-Instruct and Mistral Large 2.1 publishes its weights (Llama 3.2 Community License) 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-3.2-90B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Mistral Large 2.1 Nov 2024, Claude Haiku 3.5 Jul 31, 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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