o3-pro vs Llama-3.2-3B vs Claude Opus 4.1
Llama-3.2-3B comes out ahead, 49 to 27 and 27 on our weighted score, and it is the cheaper option too.
OpenAIo3-pro
27/100- ECI147.4
- Price$20.00 / $80.00
- Context200K
- Our pick
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
AnthropicClaude Opus 4.1
27/100- ECI144.1
- Price$15.00 / $75.00
- Context200K
Llama-3.2-3B is our pick
Llama-3.2-3B is the better all-round choice, scoring 49/100 against o3-pro (27) and Claude Opus 4.1 (27). It leads on price. 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-3.2-3BLlama-3.2-3B $0.159 · Claude Opus 4.1 $30.00 · o3-pro $35.00 per 1M tokens (3:1 blend)
- Longest contexto3-pro and Claude Opus 4.1o3-pro 200,000 · Claude Opus 4.1 200,000 · Llama-3.2-3B 131,072 tokens
- Widest inputsClaude Opus 4.1o3-pro: Text, Images · Llama-3.2-3B: Text · Claude Opus 4.1: Text, Images, PDFs
- Self-hostingLlama-3.2-3BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | o3-pro | Llama-3.2-3B | Claude Opus 4.1 |
|---|---|---|---|---|
| Price | 50% | 0 | 88 | 0 |
| Inputs & features | 30% | 70 | 0 | 70 |
| Context window | 20% | 32 | 24 | 32 |
| Overall | 100% | 27/100 | 49/100 | 27/100 |
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 | o3-proOpenAI | Llama-3.2-3BMeta | Claude Opus 4.1Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 147.4 (best) | — | 144.1 |
| ECI rank | #60 of 148 (best) | — | #81 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 77.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 12.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 68.9% |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 73.4% |
| Price per million tokens | |||
| Input | $20.00 | $0.10 (best) | $15.00 |
| Output | $80.00 | $0.335 (best) | $75.00 |
| Cached input | — | — | — |
| Blended (3:1) | $35.00 | $0.159 (best) | $30.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 3 providers | Median of 14 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 131,072 tokens | 200,000 tokens (best) |
| Max output | 100,000 tokens (best) | 8,192 tokens | 32,000 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 | Yeslow · medium · high | No | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenLlama 3.2 Community License | Proprietary |
| API model ID | o3-pro | — | — |
| API providers | 6 | 3 | 14 (best) |
| Released | Jun 10, 2025 | Sep 25, 2024 | Aug 5, 2025 |
| Knowledge cutoff | May 2024 | Dec 2023 | Mar 31, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o3-pro$360.00
- Llama-3.2-3B$1.67
- Claude Opus 4.1$300.00
Which should you choose?
Which is better: o3-pro, Llama-3.2-3B or Claude Opus 4.1?
Llama-3.2-3B is the better all-round choice, scoring 49/100 against o3-pro (27) and Claude Opus 4.1 (27). It leads on price. 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, o3-pro, Llama-3.2-3B or Claude Opus 4.1?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). Claude Opus 4.1 costs $15.00 input / $75.00 output per million tokens (median across 14 API providers); o3-pro costs $20.00 input / $80.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.159 per million tokens for Llama-3.2-3B versus $30.00 for Claude Opus 4.1 (189× as much) and $35.00 for o3-pro (220× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. o3-pro has an ECI of 147.4, Llama-3.2-3B has not been scored yet and Claude Opus 4.1 has an ECI of 144.1.
Which is better for coding?
There are no published SWE-bench Verified results for o3-pro and Llama-3.2-3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-3B does not support tool calling, which most coding agents need.
Which has the bigger context window?
o3-pro and Claude Opus 4.1 have the largest context windows (200,000 and 200,000 tokens), against 131,072 for Llama-3.2-3B. Maximum output per response: o3-pro up to 100,000, Llama-3.2-3B up to 8,192, Claude Opus 4.1 up to 32,000 tokens.
Which can read images, PDFs, audio or video?
o3-pro accepts text and images; Llama-3.2-3B accepts text; Claude Opus 4.1 accepts text, images and PDFs. Claude Opus 4.1 handles the widest range of inputs.
Are any of these open source?
Llama-3.2-3B publishes its weights (Llama 3.2 Community License) and can be self-hosted; o3-pro and Claude Opus 4.1 is proprietary.
Which is newer?
Claude Opus 4.1 is the newest, released Aug 5, 2025. o3-pro came out Jun 10, 2025; Llama-3.2-3B came out Sep 25, 2024. Knowledge cutoff: o3-pro May 2024, Llama-3.2-3B Dec 2023, Claude Opus 4.1 Mar 31, 2025.
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.
