Claude Opus 4.8 vs GPT-5.3 Codex vs GPT-5.5
Too close to call on our weighted score (GPT-5.3 Codex 64, GPT-5.5 63, Claude Opus 4.8 63). The right pick depends on what you value most.
AnthropicClaude Opus 4.8
63/100- ECI158.3
- Price$5.00 / $25.00
- Context1M
OpenAIGPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
- OpenAI
GPT-5.5
63/100- ECI159.2
- Price$5.00 / $30.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 1 points (GPT-5.3 Codex 64/100, GPT-5.5 63/100, Claude Opus 4.8 63/100), so choose by what matters most for your work: GPT-5.5 for raw capability and GPT-5.3 Codex on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.5Capabilities Index (ECI): GPT-5.5 159.2 · Claude Opus 4.8 158.3 · GPT-5.3 Codex 156.8
- Lowest priceGPT-5.3 CodexGPT-5.3 Codex $4.81 · Claude Opus 4.8 $10.00 · GPT-5.5 $11.25 per 1M tokens (3:1 blend)
- Longest contextGPT-5.5GPT-5.5 1,050,000 · Claude Opus 4.8 1,000,000 · GPT-5.3 Codex 400,000 tokens
- Widest inputsSame inputsClaude Opus 4.8: Text, Images, PDFs · GPT-5.3 Codex: Text, Images, PDFs · GPT-5.5: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Claude Opus 4.8 | GPT-5.3 Codex | GPT-5.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 89 | 87 | 90 |
| Price | 25% | 2 | 18 | 0 |
| Inputs & features | 15% | 80 | 80 | 80 |
| Context window | 10% | 60 | 44 | 61 |
| Overall | 100% | 63/100 | 64/100 | 63/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Opus 4.8Anthropic | GPT-5.3 CodexOpenAI | GPT-5.5OpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 158.3 | 156.8 | 159.2 (best) |
| ECI rank | #12 of 148 | #18 of 148 | #10 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 91.0% | — | 94.0% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 80.0% | — | 85.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 98.3% | — | 100% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | 80.6% (best) |
| SimpleQA VerifiedShort factual questions | 53.0% | — | 63.0% (best) |
| Price per million tokens | |||
| Input | $5.00 | $1.75 (best) | $5.00 |
| Output | $25.00 | $14.00 (best) | $30.00 |
| Cached input | $0.50 | $0.175 (best) | $0.50 |
| Blended (3:1) | $10.00 | $4.81 (best) | $11.25 |
| Long-context rate | Same rate | Same rate | Over 272K: $10.00 / $45.00 |
| Price source | Official Anthropic API | Official OpenAI API | Official OpenAI API |
| Limits | |||
| Context window | 1,000,000 tokens | 400,000 tokens | 1,050,000 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 | Yes | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh | Yeslow · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | claude-opus-4-8 | gpt-5.3-codex | gpt-5.5 |
| API providers | 45 (best) | 19 | 42 |
| Released | May 28, 2026 | Feb 5, 2026 | Apr 23, 2026 |
| Knowledge cutoff | Jan 2026 | Aug 31, 2025 | Dec 1, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Opus 4.8$100.00
- GPT-5.3 Codex$45.50
- GPT-5.5$110.00
Which should you choose?
Which is better: Claude Opus 4.8, GPT-5.3 Codex or GPT-5.5?
It is close. Our weighted score puts them within 1 points (GPT-5.3 Codex 64/100, GPT-5.5 63/100, Claude Opus 4.8 63/100), so choose by what matters most for your work: GPT-5.5 for raw capability and GPT-5.3 Codex on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Opus 4.8, GPT-5.3 Codex or GPT-5.5?
GPT-5.3 Codex is cheaper at $1.75 input / $14.00 output per million tokens (official OpenAI API price). Claude Opus 4.8 costs $5.00 input / $25.00 output per million tokens (official Anthropic API price); GPT-5.5 costs $5.00 input / $30.00 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 4.8 (2.1× as much) and $11.25 for GPT-5.5 (2.3× as much).
Which scores higher on benchmarks?
GPT-5.5 scores higher on the Capabilities Index (ECI): GPT-5.5 159.2 (#10 of 148), Claude Opus 4.8 158.3 (#12 of 148) and GPT-5.3 Codex 156.8 (#18 of 148). The confidence ranges of the top two overlap (156.9–162.4 vs 156.1–160.7), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Opus 4.8 yet, so there is no like-for-like coding score. On overall capability, GPT-5.5 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?
GPT-5.5 has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Opus 4.8 and 400,000 for GPT-5.3 Codex. Maximum output per response: Claude Opus 4.8 up to 128,000, GPT-5.3 Codex up to 128,000, GPT-5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Claude Opus 4.8 accepts text, images and PDFs; GPT-5.3 Codex accepts text, images and PDFs; GPT-5.5 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
No. Claude Opus 4.8, GPT-5.3 Codex and GPT-5.5 are proprietary and only available through APIs and apps.
Which is newer?
Claude Opus 4.8 is the newest, released May 28, 2026. GPT-5.5 came out Apr 23, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: Claude Opus 4.8 Jan 2026, GPT-5.3 Codex Aug 31, 2025, GPT-5.5 Dec 1, 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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