GPT-5.6 Sol vs GPT-5.3 Codex vs Claude Opus 5
Too close to call on our weighted score (GPT-5.6 Sol 66, Claude Opus 5 66, GPT-5.3 Codex 64). The right pick depends on what you value most.
OpenAI
GPT-5.6 Sol
66/100- ECI161.8
- Price$4.00 / $20.00
- Context1.05M
OpenAI
GPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
Anthropic
Claude Opus 5
66/100- ECI162.9
- Price$5.00 / $25.00
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (GPT-5.6 Sol 66/100, Claude Opus 5 66/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: Claude Opus 5 for raw capability, GPT-5.3 Codex on price and GPT-5.6 Sol for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Opus 5Capabilities Index (ECI): Claude Opus 5 162.9 · GPT-5.6 Sol 161.8 · GPT-5.3 Codex 156.8
- Lowest priceGPT-5.3 CodexGPT-5.3 Codex $4.81 · GPT-5.6 Sol $8.00 · Claude Opus 5 $10.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 SolGPT-5.6 Sol 1,050,000 · Claude Opus 5 1,000,000 · GPT-5.3 Codex 400,000 tokens
- Widest inputsSame inputsGPT-5.6 Sol: Text, Images, PDFs · GPT-5.3 Codex: Text, Images, PDFs · Claude Opus 5: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.6 Sol | GPT-5.3 Codex | Claude Opus 5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 93 | 87 | 94 |
| Price | 25% | 7 | 18 | 2 |
| Inputs & features | 15% | 80 | 80 | 80 |
| Context window | 10% | 61 | 44 | 60 |
| Overall | 100% | 66/100 | 64/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 161.8 | 156.8 | 162.9 (best) |
| ECI rank | #8 of 148 | #18 of 148 | #5 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 93.5% | — | 93.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 89.1% (best) | — | 85.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | — | 98.9% |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | — |
| SimpleQA VerifiedShort factual questions | 69.7% (best) | — | 59.9% |
| Price per million tokens | |||
| Input | $4.00 | $1.75 (best) | $5.00 |
| Output | $20.00 | $14.00 (best) | $25.00 |
| Cached input | $0.40 | $0.175 (best) | $0.50 |
| Blended (3:1) | $8.00 | $4.81 (best) | $10.00 |
| Long-context rate | Over 272K: $8.00 / $30.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Official Anthropic API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 400,000 tokens | 1,000,000 tokens |
| 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 · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.6-sol | gpt-5.3-codex | claude-opus-5 |
| API providers | 40 (best) | 19 | 35 |
| Released | Jul 9, 2026 | Feb 5, 2026 | Jul 24, 2026 |
| Knowledge cutoff | Feb 16, 2026 | Aug 31, 2025 | May 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT-5.6 Sol$80.00
GPT-5.3 Codex$45.50
Claude Opus 5$100.00
Which should you choose?
Which is better: GPT-5.6 Sol, GPT-5.3 Codex or Claude Opus 5?
It is close. Our weighted score puts them within a point (GPT-5.6 Sol 66/100, Claude Opus 5 66/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: Claude Opus 5 for raw capability, GPT-5.3 Codex on price and GPT-5.6 Sol for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5.6 Sol, GPT-5.3 Codex or Claude Opus 5?
GPT-5.3 Codex is cheaper at $1.75 input / $14.00 output per million tokens (official OpenAI API price). GPT-5.6 Sol costs $4.00 input / $20.00 output per million tokens (official OpenAI API price); Claude Opus 5 costs $5.00 input / $25.00 output per million tokens (official Anthropic 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 $8.00 for GPT-5.6 Sol (1.7× as much) and $10.00 for Claude Opus 5 (2.1× as much).
Which scores higher on benchmarks?
Claude Opus 5 scores higher on the Capabilities Index (ECI): Claude Opus 5 162.9 (#5 of 148), GPT-5.6 Sol 161.8 (#8 of 148) and GPT-5.3 Codex 156.8 (#18 of 148). The confidence ranges of the top two overlap (160.2–166.7 vs 159.3–165.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Sol and Claude Opus 5 yet, so there is no like-for-like coding score. On overall capability, Claude Opus 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-5.6 Sol has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Opus 5 and 400,000 for GPT-5.3 Codex. Maximum output per response: GPT-5.6 Sol up to 128,000, GPT-5.3 Codex up to 128,000, Claude Opus 5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Sol accepts text, images and PDFs; GPT-5.3 Codex accepts text, images and PDFs; Claude Opus 5 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
No. GPT-5.6 Sol, GPT-5.3 Codex and Claude Opus 5 are proprietary and only available through APIs and apps.
Which is newer?
Claude Opus 5 is the newest, released Jul 24, 2026. GPT-5.6 Sol came out Jul 9, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: GPT-5.6 Sol Feb 16, 2026, GPT-5.3 Codex Aug 31, 2025, Claude Opus 5 May 2026.
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.