GPT-5-Codex vs o3
Too close to call on our weighted score (o3 42, GPT-5-Codex 42). The right pick depends on what you value most.
OpenAIGPT-5-Codex
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
- OpenAI
o3
42/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (o3 42/100, GPT-5-Codex 42/100), so choose by what matters most for your work: GPT-5-Codex on price and GPT-5-Codex for long inputs. 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 priceGPT-5-CodexGPT-5-Codex $3.44 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextGPT-5-CodexGPT-5-Codex 400,000 · o3 200,000 tokens
- Widest inputso3GPT-5-Codex: Text, Images · o3: Text, Images, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GPT-5-Codex | o3 |
|---|---|---|---|
| Price | 50% | 24 | 24 |
| Inputs & features | 30% | 70 | 80 |
| Context window | 20% | 44 | 32 |
| Overall | 100% | 42/100 | 42/100 |
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 | GPT-5-CodexOpenAI | o3OpenAI |
|---|---|---|
| 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 | $1.25 (best) | $2.00 |
| Output | $10.00 | $8.00 (best) |
| Cached input | — | $0.50 |
| Blended (3:1) | $3.44 (best) | $3.50 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official OpenAI API |
| Limits | ||
| Context window | 400,000 tokens (best) | 200,000 tokens |
| Max output | 128,000 tokens (best) | 100,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yeslow · medium · high |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | o3 |
| API providers | 3 | 18 (best) |
| Released | Sep 15, 2025 | Apr 16, 2025 |
| Knowledge cutoff | Sep 30, 2024 | May 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5-Codex$32.50
- o3$36.00
Which should you choose?
Which is better: GPT-5-Codex or o3?
It is close. Our weighted score puts them within a point (o3 42/100, GPT-5-Codex 42/100), so choose by what matters most for your work: GPT-5-Codex on price and GPT-5-Codex for long inputs. 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, GPT-5-Codex or o3?
GPT-5-Codex is cheaper at $1.25 input / $10.00 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 $3.44 per million tokens for GPT-5-Codex versus $3.50 for o3 (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GPT-5-Codex has not been scored yet and o3 has an ECI of 146.9.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5-Codex yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
GPT-5-Codex has the largest context window at 400,000 tokens, against 200,000 for o3. Maximum output per response: GPT-5-Codex up to 128,000, o3 up to 100,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5-Codex accepts text and images; o3 accepts text, images and PDFs. o3 handles the widest range of inputs.
Are any of these open source?
No. GPT-5-Codex and o3 are proprietary and only available through APIs and apps.
Which is newer?
GPT-5-Codex is the newest, released Sep 15, 2025. o3 came out Apr 16, 2025. Knowledge cutoff: GPT-5-Codex Sep 30, 2024, o3 May 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 Oct 4, 2026.
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