GPT-5.6 Sol vs Mercury Edit 2 vs Claude Opus 5
Too close to call on our weighted score (GPT-5.6 Sol 40, Claude Opus 5 37, Mercury Edit 2 35). The right pick depends on what you value most.
OpenAIGPT-5.6 Sol
40/100- ECI161.8
- Price$4.00 / $20.00
- Context1.05M
InceptionMercury Edit 2
35/100- ECI—
- Price$0.25 / $0.75
- Context32K
AnthropicClaude Opus 5
37/100- ECI162.9
- Price$5.00 / $25.00
- Context1M
Too close to call
It is close. Our weighted score puts them within 2 points (GPT-5.6 Sol 40/100, Claude Opus 5 37/100, Mercury Edit 2 35/100), so choose by what matters most for your work: Mercury Edit 2 on price and GPT-5.6 Sol 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 priceMercury Edit 2Mercury Edit 2 $0.375 · 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 · Mercury Edit 2 32,000 tokens
- Widest inputsGPT-5.6 Sol and Claude Opus 5GPT-5.6 Sol: Text, Images, PDFs · Mercury Edit 2: Text · Claude Opus 5: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.6 Sol | Mercury Edit 2 | Claude Opus 5 |
|---|---|---|---|---|
| Price | 50% | 7 | 70 | 2 |
| Inputs & features | 30% | 80 | 0 | 80 |
| Context window | 20% | 61 | 0 | 60 |
| Overall | 100% | 40/100 | 35/100 | 37/100 |
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-5.6 SolOpenAI | Mercury Edit 2Inception | Claude Opus 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 161.8 | — | 162.9 (best) |
| ECI rank | #8 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% |
| SimpleQA VerifiedShort factual questions | 69.7% (best) | — | 59.9% |
| Price per million tokens | |||
| Input | $4.00 | $0.25 (best) | $5.00 |
| Output | $20.00 | $0.75 (best) | $25.00 |
| Cached input | $0.40 | $0.025 (best) | $0.50 |
| Blended (3:1) | $8.00 | $0.375 (best) | $10.00 |
| Long-context rate | Over 272K: $8.00 / $30.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Official Inception API | Official Anthropic API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 32,000 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens (best) | 8,192 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | No | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | No | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.6-sol | mercury-edit-2 | claude-opus-5 |
| API providers | 40 (best) | 1 | 35 |
| Released | Jul 9, 2026 | Mar 30, 2026 | Jul 24, 2026 |
| Knowledge cutoff | Feb 16, 2026 | — | 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
- Mercury Edit 2$4.00
- Claude Opus 5$100.00
Which should you choose?
Which is better: GPT-5.6 Sol, Mercury Edit 2 or Claude Opus 5?
It is close. Our weighted score puts them within 2 points (GPT-5.6 Sol 40/100, Claude Opus 5 37/100, Mercury Edit 2 35/100), so choose by what matters most for your work: Mercury Edit 2 on price and GPT-5.6 Sol 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-5.6 Sol, Mercury Edit 2 or Claude Opus 5?
Mercury Edit 2 is cheaper at $0.25 input / $0.75 output per million tokens (official Inception 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 $0.375 per million tokens for Mercury Edit 2 versus $8.00 for GPT-5.6 Sol (21× as much) and $10.00 for Claude Opus 5 (27× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.6 Sol has an ECI of 161.8, Mercury Edit 2 has not been scored yet and Claude Opus 5 has an ECI of 162.9.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Sol, Mercury Edit 2 and Claude Opus 5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Mercury Edit 2 does not support tool calling, which most coding agents need.
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 32,000 for Mercury Edit 2. Maximum output per response: GPT-5.6 Sol up to 128,000, Mercury Edit 2 up to 8,192, 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; Mercury Edit 2 accepts text; Claude Opus 5 accepts text, images and PDFs. GPT-5.6 Sol handles the widest range of inputs.
Are any of these open source?
No. GPT-5.6 Sol, Mercury Edit 2 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; Mercury Edit 2 came out Mar 30, 2026. Knowledge cutoff: GPT-5.6 Sol Feb 16, 2026, 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.
