GPT-5.2 Pro vs GPT-5.3 Codex vs Claude Opus 4.6
GPT-5.3 Codex comes out ahead, 64 to 61 and 56 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.2 Pro
56/100- ECI155.4
- Price$21.00 / $168.00
- Context400K
- Our pickOpenAI
GPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
AnthropicClaude Opus 4.6
61/100- ECI155.3
- Price$5.00 / $25.00
- Context1M
GPT-5.3 Codex is our pick
GPT-5.3 Codex is the better all-round choice, scoring 64/100 against Claude Opus 4.6 (61) and GPT-5.2 Pro (56). It leads on capability and price. Claude Opus 4.6 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.3 CodexCapabilities Index (ECI): GPT-5.3 Codex 156.8 · GPT-5.2 Pro 155.4 · Claude Opus 4.6 155.3
- Lowest priceGPT-5.3 CodexGPT-5.3 Codex $4.81 · Claude Opus 4.6 $10.00 · GPT-5.2 Pro $57.75 per 1M tokens (3:1 blend)
- Longest contextClaude Opus 4.6Claude Opus 4.6 1,000,000 · GPT-5.2 Pro 400,000 · GPT-5.3 Codex 400,000 tokens
- Widest inputsGPT-5.3 Codex and Claude Opus 4.6GPT-5.2 Pro: Text, Images · GPT-5.3 Codex: Text, Images, PDFs · Claude Opus 4.6: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.2 Pro | GPT-5.3 Codex | Claude Opus 4.6 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 85 | 87 | 85 |
| Price | 25% | 0 | 18 | 2 |
| Inputs & features | 15% | 60 | 80 | 80 |
| Context window | 10% | 44 | 44 | 60 |
| Overall | 100% | 56/100 | 64/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.2 ProOpenAI | GPT-5.3 CodexOpenAI | Claude Opus 4.6Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.4 | 156.8 (best) | 155.3 |
| ECI rank | #25 of 148 | #18 of 148 (best) | #27 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 90.5% |
| FrontierMath Tiers 1–3Research-level mathematics | 74.0% (best) | — | 66.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 94.4% |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | 78.7% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 47.0% |
| Price per million tokens | |||
| Input | $21.00 | $1.75 (best) | $5.00 |
| Output | $168.00 | $14.00 (best) | $25.00 |
| Cached input | — | $0.175 (best) | $0.50 |
| Blended (3:1) | $57.75 | $4.81 (best) | $10.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Official Anthropic API |
| Limits | |||
| Context window | 400,000 tokens | 400,000 tokens | 1,000,000 tokens (best) |
| Max output | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yesmedium · high · xhigh | Yeslow · medium · high · xhigh | Yeslow · medium · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.2-pro | gpt-5.3-codex | claude-opus-4-6 |
| API providers | 8 | 19 | 33 (best) |
| Released | Dec 11, 2025 | Feb 5, 2026 | Feb 5, 2026 |
| Knowledge cutoff | Aug 31, 2025 | Aug 31, 2025 | May 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.
- GPT-5.2 Pro$546.00
- GPT-5.3 Codex$45.50
- Claude Opus 4.6$100.00
Which should you choose?
Which is better: GPT-5.2 Pro, GPT-5.3 Codex or Claude Opus 4.6?
GPT-5.3 Codex is the better all-round choice, scoring 64/100 against Claude Opus 4.6 (61) and GPT-5.2 Pro (56). It leads on capability and price. Claude Opus 4.6 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5.2 Pro, GPT-5.3 Codex or Claude Opus 4.6?
GPT-5.3 Codex is cheaper at $1.75 input / $14.00 output per million tokens (official OpenAI API price). Claude Opus 4.6 costs $5.00 input / $25.00 output per million tokens (official Anthropic API price); GPT-5.2 Pro costs $21.00 input / $168.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $4.81 per million tokens for GPT-5.3 Codex versus $10.00 for Claude Opus 4.6 (2.1× as much) and $57.75 for GPT-5.2 Pro (12× as much).
Which scores higher on benchmarks?
GPT-5.3 Codex scores higher on the Capabilities Index (ECI): GPT-5.3 Codex 156.8 (#18 of 148), GPT-5.2 Pro 155.4 (#25 of 148) and Claude Opus 4.6 155.3 (#27 of 148). The confidence ranges of the top two overlap (153.5–160.8 vs 153.0–158.2), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.2 Pro yet, so there is no like-for-like coding score. On overall capability, GPT-5.3 Codex 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 Opus 4.6 has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.2 Pro and 400,000 for GPT-5.3 Codex. Maximum output per response: GPT-5.2 Pro up to 128,000, GPT-5.3 Codex up to 128,000, Claude Opus 4.6 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.2 Pro accepts text and images; GPT-5.3 Codex accepts text, images and PDFs; Claude Opus 4.6 accepts text, images and PDFs. GPT-5.3 Codex handles the widest range of inputs.
Are any of these open source?
No. GPT-5.2 Pro, GPT-5.3 Codex and Claude Opus 4.6 are proprietary and only available through APIs and apps.
Which is newer?
GPT-5.3 Codex is the newest, released Feb 5, 2026. Claude Opus 4.6 came out Feb 5, 2026; GPT-5.2 Pro came out Dec 11, 2025. Knowledge cutoff: GPT-5.2 Pro Aug 31, 2025, GPT-5.3 Codex Aug 31, 2025, Claude Opus 4.6 May 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.
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