o3 vs Llama-3.2-3B
Llama-3.2-3B comes out ahead, 49 to 42 on our weighted score, and it is the cheaper option too.
OpenAIo3
42/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
- Our pick
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Add a model
Make it a three-way comparison.
Llama-3.2-3B is our pick
Llama-3.2-3B is the better all-round choice, scoring 49/100 against o3 (42). It leads on price. o3 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-3.2-3BLlama-3.2-3B $0.159 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contexto3o3 200,000 · Llama-3.2-3B 131,072 tokens
- Widest inputso3o3: Text, Images, PDFs · Llama-3.2-3B: Text
- Self-hostingLlama-3.2-3BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | o3 | Llama-3.2-3B |
|---|---|---|---|
| Price | 50% | 24 | 88 |
| Inputs & features | 30% | 80 | 0 |
| Context window | 20% | 32 | 24 |
| Overall | 100% | 42/100 | 49/100 |
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 | o3OpenAI | Llama-3.2-3BMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 146.9 | — |
| ECI rank | #63 of 148 | — |
| GPQA DiamondGraduate-level science questions | 81.8% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 33.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.4% | — |
| SWE-bench VerifiedFixing real GitHub issues | 62.3% | — |
| SimpleQA VerifiedShort factual questions | 49.4% | — |
| Price per million tokens | ||
| Input | $2.00 | $0.10 (best) |
| Output | $8.00 | $0.335 (best) |
| Cached input | $0.50 | — |
| Blended (3:1) | $3.50 | $0.159 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 3 providers |
| Limits | ||
| Context window | 200,000 tokens (best) | 131,072 tokens |
| Max output | 100,000 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | No |
| Tool calling | Yes | No |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | OpenLlama 3.2 Community License |
| API model ID | o3 | — |
| API providers | 18 (best) | 3 |
| Released | Apr 16, 2025 | Sep 25, 2024 |
| Knowledge cutoff | May 2024 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o3$36.00
- Llama-3.2-3B$1.67
Which should you choose?
Which is better: o3 or Llama-3.2-3B?
Llama-3.2-3B is the better all-round choice, scoring 49/100 against o3 (42). It leads on price. o3 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, o3 or Llama-3.2-3B?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). o3 costs $2.00 input / $8.00 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 $3.50 for o3 (22× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. o3 has an ECI of 146.9 and Llama-3.2-3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for 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 has the largest context window at 200,000 tokens, against 131,072 for Llama-3.2-3B. Maximum output per response: o3 up to 100,000, Llama-3.2-3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
o3 accepts text, images and PDFs; Llama-3.2-3B accepts text. o3 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 is proprietary.
Which is newer?
o3 is the newest, released Apr 16, 2025. Llama-3.2-3B came out Sep 25, 2024. Knowledge cutoff: o3 May 2024, Llama-3.2-3B Dec 2023.
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.
