GPT-5.6 Cyber vs Macaron V1 Venti vs Claude Mythos 5
Macaron V1 Venti comes out ahead, 44 to 33 and 30 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.6 Cyber
30/100- ECI—
- Price$12.50 / $75.00
- Context400K
- Our pick
Mindlab
Macaron V1 Venti
44/100- ECI—
- Price$0.825 / $2.48
- Context1.05M
AnthropicClaude Mythos 5
33/100- ECI—
- Price$10.00 / $50.00
- Context1M
Macaron V1 Venti is our pick
Macaron V1 Venti is the better all-round choice, scoring 44/100 against Claude Mythos 5 (33) and GPT-5.6 Cyber (30). It leads on price. 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 priceMacaron V1 VentiMacaron V1 Venti $1.24 · Claude Mythos 5 $20.00 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextMacaron V1 VentiMacaron V1 Venti 1,048,576 · Claude Mythos 5 1,000,000 · GPT-5.6 Cyber 400,000 tokens
- Widest inputsClaude Mythos 5GPT-5.6 Cyber: Text, Images · Macaron V1 Venti: Text · Claude Mythos 5: Text, Images, PDFs
- Self-hostingMacaron V1 VentiPublishes downloadable weights (MIT)
| Measure | Weight | GPT-5.6 Cyber | Macaron V1 Venti | Claude Mythos 5 |
|---|---|---|---|---|
| Price | 50% | 0 | 44 | 0 |
| Inputs & features | 30% | 70 | 35 | 70 |
| Context window | 20% | 44 | 61 | 60 |
| Overall | 100% | 30/100 | 44/100 | 33/100 |
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 CyberOpenAI | Macaron V1 VentiMindlab | Claude Mythos 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $12.50 | $0.825 (best) | $10.00 |
| Output | $75.00 | $2.48 (best) | $50.00 |
| Cached input | $1.25 | — | — |
| Blended (3:1) | $28.13 | $1.24 (best) | $20.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 1 providers | Median of 2 providers |
| Limits | |||
| Context window | 400,000 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 128,000 tokens | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenMIT | Proprietary |
| API model ID | gpt-daybreak-red-latest | — | — |
| API providers | 1 | 1 | 2 (best) |
| Released | Aug 7, 2026 | Jul 21, 2026 | Jun 9, 2026 |
| Knowledge cutoff | Feb 16, 2026 | — | Jan 31, 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 Cyber$275.00
- Macaron V1 Venti$13.20
- Claude Mythos 5$200.00
Which should you choose?
Which is better: GPT-5.6 Cyber, Macaron V1 Venti or Claude Mythos 5?
Macaron V1 Venti is the better all-round choice, scoring 44/100 against Claude Mythos 5 (33) and GPT-5.6 Cyber (30). It leads on price. 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 Cyber, Macaron V1 Venti or Claude Mythos 5?
Macaron V1 Venti is cheaper at $0.825 input / $2.48 output per million tokens (median across 1 API provider). Claude Mythos 5 costs $10.00 input / $50.00 output per million tokens (median across 2 API providers); GPT-5.6 Cyber costs $12.50 input / $75.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.24 per million tokens for Macaron V1 Venti versus $20.00 for Claude Mythos 5 (16× as much) and $28.13 for GPT-5.6 Cyber (23× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.6 Cyber has not been scored yet, Macaron V1 Venti has not been scored yet and Claude Mythos 5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Cyber, Macaron V1 Venti and Claude Mythos 5 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?
Macaron V1 Venti has the largest context window at 1,048,576 tokens, against 1,000,000 for Claude Mythos 5 and 400,000 for GPT-5.6 Cyber. Maximum output per response: GPT-5.6 Cyber up to 128,000, Macaron V1 Venti up to 131,072, Claude Mythos 5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Cyber accepts text and images; Macaron V1 Venti accepts text; Claude Mythos 5 accepts text, images and PDFs. Claude Mythos 5 handles the widest range of inputs.
Are any of these open source?
Macaron V1 Venti publishes its weights (MIT) and can be self-hosted; GPT-5.6 Cyber and Claude Mythos 5 is proprietary.
Which is newer?
GPT-5.6 Cyber is the newest, released Aug 7, 2026. Macaron V1 Venti came out Jul 21, 2026; Claude Mythos 5 came out Jun 9, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026, Claude Mythos 5 Jan 31, 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 Nov 2, 2026.
