GPT-5.5 vs Claude Mythos 5 vs Claude Opus 4.8
Too close to call on our weighted score (Claude Opus 4.8 37, GPT-5.5 36, Claude Mythos 5 36). The right pick depends on what you value most.
OpenAIGPT-5.5
36/100- ECI159.2
- Price$5.00 / $30.00
- Context1.05M
AnthropicClaude Mythos 5
36/100- ECI—
- Price$10.00 / $50.00
- Context1M
- Anthropic
Claude Opus 4.8
37/100- ECI158.3
- Price$5.00 / $25.00
- Context1M
Too close to call
It is close. Our weighted score puts them within 1 points (Claude Opus 4.8 37/100, GPT-5.5 36/100, Claude Mythos 5 36/100), so choose by what matters most for your work: Claude Opus 4.8 on price and GPT-5.5 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 priceClaude Opus 4.8Claude Opus 4.8 $10.00 · GPT-5.5 $11.25 · Claude Mythos 5 $20.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.5GPT-5.5 1,050,000 · Claude Mythos 5 1,000,000 · Claude Opus 4.8 1,000,000 tokens
- Widest inputsSame inputsGPT-5.5: Text, Images, PDFs · Claude Mythos 5: Text, Images, PDFs · Claude Opus 4.8: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.5 | Claude Mythos 5 | Claude Opus 4.8 |
|---|---|---|---|---|
| Price | 50% | 0 | 0 | 2 |
| Inputs & features | 30% | 80 | 80 | 80 |
| Context window | 20% | 61 | 60 | 60 |
| Overall | 100% | 36/100 | 36/100 | 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-5.5OpenAI | Claude Mythos 5Anthropic | Claude Opus 4.8Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 159.2 (best) | — | 158.3 |
| ECI rank | #10 of 148 (best) | — | #12 of 148 |
| GPQA DiamondGraduate-level science questions | 94.0% (best) | — | 91.0% |
| FrontierMath Tiers 1–3Research-level mathematics | 85.3% (best) | — | 80.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | — | 98.3% |
| SWE-bench VerifiedFixing real GitHub issues | 80.6% | — | — |
| SimpleQA VerifiedShort factual questions | 63.0% (best) | — | 53.0% |
| Price per million tokens | |||
| Input | $5.00 (best) | $10.00 | $5.00 (best) |
| Output | $30.00 | $50.00 | $25.00 (best) |
| Cached input | $0.50 | — | $0.50 |
| Blended (3:1) | $11.25 | $20.00 | $10.00 (best) |
| Long-context rate | Over 272K: $10.00 / $45.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 2 providers | Official Anthropic API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,000,000 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 | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.5 | — | claude-opus-4-8 |
| API providers | 42 | 2 | 45 (best) |
| Released | Apr 23, 2026 | Jun 9, 2026 | May 28, 2026 |
| Knowledge cutoff | Dec 1, 2025 | Jan 31, 2026 | Jan 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-5.5$110.00
- Claude Mythos 5$200.00
- Claude Opus 4.8$100.00
Which should you choose?
Which is better: GPT-5.5, Claude Mythos 5 or Claude Opus 4.8?
It is close. Our weighted score puts them within 1 points (Claude Opus 4.8 37/100, GPT-5.5 36/100, Claude Mythos 5 36/100), so choose by what matters most for your work: Claude Opus 4.8 on price and GPT-5.5 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-5.5, Claude Mythos 5 or Claude Opus 4.8?
Claude Opus 4.8 is cheaper at $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); Claude Mythos 5 costs $10.00 input / $50.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $10.00 per million tokens for Claude Opus 4.8 versus $11.25 for GPT-5.5 (1.1× as much) and $20.00 for Claude Mythos 5 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.5 has an ECI of 159.2, Claude Mythos 5 has not been scored yet and Claude Opus 4.8 has an ECI of 158.3.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Mythos 5 and Claude Opus 4.8 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. 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 Mythos 5 and 1,000,000 for Claude Opus 4.8. Maximum output per response: GPT-5.5 up to 128,000, Claude Mythos 5 up to 128,000, Claude Opus 4.8 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.5 accepts text, images and PDFs; Claude Mythos 5 accepts text, images and PDFs; Claude Opus 4.8 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
No. GPT-5.5, Claude Mythos 5 and Claude Opus 4.8 are proprietary and only available through APIs and apps.
Which is newer?
Claude Mythos 5 is the newest, released Jun 9, 2026. Claude Opus 4.8 came out May 28, 2026; GPT-5.5 came out Apr 23, 2026. Knowledge cutoff: GPT-5.5 Dec 1, 2025, Claude Mythos 5 Jan 31, 2026, Claude Opus 4.8 Jan 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.
