Llama-3.2-90B-Vision-Instruct vs Llama-3.2-11B-Vision-Instruct vs Claude Haiku 3.5
Claude Haiku 3.5 comes out ahead, 49 to 40 and 40 on our weighted score, though Llama-3.2-11B-Vision-Instruct is 13× cheaper per token.
MetaLlama-3.2-90B-Vision-Instruct
40/100- ECI125.5
- Price—
- Context128K
- Meta
Llama-3.2-11B-Vision-Instruct
40/100- ECI—
- Price$0.055 / $0.345
- Context128K
- Our pick
AnthropicClaude Haiku 3.5
49/100- 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 49/100 against Llama-3.2-90B-Vision-Instruct (40) and Llama-3.2-11B-Vision-Instruct (40). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.2-90B-Vision-Instruct 128,000 · Llama-3.2-11B-Vision-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Llama-3.2-90B-Vision-Instruct: Text, Images · Llama-3.2-11B-Vision-Instruct: Text, Images · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingLlama-3.2-90B-Vision-Instruct and Llama-3.2-11B-Vision-InstructPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Llama-3.2-11B-Vision-Instruct | Claude Haiku 3.5 |
|---|---|---|---|---|
| Inputs & features | 60% | 50 | 50 | 60 |
| Context window | 40% | 24 | 24 | 32 |
| Overall | 100% | 40/100 | 40/100 | 49/100 |
Left out because at least one model lacks the data: capability and 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 | Llama-3.2-11B-Vision-InstructMeta | Claude Haiku 3.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 125.5 | — | 127.0 (best) |
| ECI rank | #150 of 165 | — | #147 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 41.0% (best) | — | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% | — | 4.3% (best) |
| Price per million tokens | |||
| Input | — | $0.055 (best) | $0.80 |
| Output | — | $0.345 (best) | $4.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.128 (best) | $1.60 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 3 providers | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 200,000 tokens (best) |
| Max output | 4,096 tokens | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | 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 | 4 (best) | 4 (best) |
| Released | Sep 25, 2024 | Sep 25, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 2023 | 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—
- Llama-3.2-11B-Vision-Instruct$1.24
- Claude Haiku 3.5$16.00
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct, Llama-3.2-11B-Vision-Instruct or Claude Haiku 3.5?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Llama-3.2-90B-Vision-Instruct (40) and Llama-3.2-11B-Vision-Instruct (40). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Llama-3.2-90B-Vision-Instruct, Llama-3.2-11B-Vision-Instruct or Claude Haiku 3.5?
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). 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). Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.2-90B-Vision-Instruct has an ECI of 125.5, Llama-3.2-11B-Vision-Instruct has not been scored yet and Claude Haiku 3.5 has an ECI of 127.0.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct, Llama-3.2-11B-Vision-Instruct and Claude Haiku 3.5 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 128,000 for Llama-3.2-90B-Vision-Instruct and 128,000 for Llama-3.2-11B-Vision-Instruct. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Llama-3.2-11B-Vision-Instruct up to 4,096, 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; Llama-3.2-11B-Vision-Instruct accepts text and images; 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 Llama-3.2-11B-Vision-Instruct publishes its weights (Llama 3.2 Community License) and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Claude Haiku 3.5 is the newest, released Oct 22, 2024. Llama-3.2-90B-Vision-Instruct came out Sep 25, 2024; Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Llama-3.2-11B-Vision-Instruct Dec 2023, 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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