GPT-6 Astra (Fast) vs Macaron V1 Venti vs Claude Mythos 5.1
Too close to call on our weighted score (GPT-6 Astra (Fast) 66, Claude Mythos 5.1 66, Macaron V1 Venti 45). The right pick depends on what you value most.
OpenAIGPT-6 Astra (Fast)
66/100- ECI—
- Price$20.00 / $100.00
- Context1.05M
Mindlab
Macaron V1 Venti
45/100- ECI—
- Price$0.825 / $2.48
- Context1.05M
AnthropicClaude Mythos 5.1
66/100- ECI—
- Price—
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (GPT-6 Astra (Fast) 66/100, Claude Mythos 5.1 66/100, Macaron V1 Venti 45/100), so choose by what matters most for your work: Macaron V1 Venti on price. The score weighs inputs & features 60%, context window 40%. 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 · GPT-6 Astra (Fast) $40.00 per 1M tokens (3:1 blend) · Claude Mythos 5.1 unpriced
- Longest contextGPT-6 Astra (Fast) and Macaron V1 VentiGPT-6 Astra (Fast) 1,050,000 · Macaron V1 Venti 1,048,576 · Claude Mythos 5.1 1,000,000 tokens
- Widest inputsGPT-6 Astra (Fast) and Claude Mythos 5.1GPT-6 Astra (Fast): Text, Images, PDFs · Macaron V1 Venti: Text · Claude Mythos 5.1: Text, Images, PDFs
- Self-hostingMacaron V1 VentiPublishes downloadable weights (MIT)
| Measure | Weight | GPT-6 Astra (Fast) | Macaron V1 Venti | Claude Mythos 5.1 |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 35 | 70 |
| Context window | 40% | 61 | 61 | 60 |
| Overall | 100% | 66/100 | 45/100 | 66/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-6 Astra (Fast)OpenAI | Macaron V1 VentiMindlab | Claude Mythos 5.1Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $20.00 | $0.825 (best) | — |
| Output | $100.00 | $2.48 (best) | — |
| Cached input | — | — | — |
| Blended (3:1) | $40.00 | $1.24 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 1 providers | Median of 1 providers | — |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens | 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 | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenMIT | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 1 | — |
| Released | Sep 4, 2026 | Jul 21, 2026 | Sep 1, 2026 |
| Knowledge cutoff | — | — | Jun 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-6 Astra (Fast)$400.00
- Macaron V1 Venti$13.20
- Claude Mythos 5.1—
Which should you choose?
Which is better: GPT-6 Astra (Fast), Macaron V1 Venti or Claude Mythos 5.1?
It is close. Our weighted score puts them within a point (GPT-6 Astra (Fast) 66/100, Claude Mythos 5.1 66/100, Macaron V1 Venti 45/100), so choose by what matters most for your work: Macaron V1 Venti on price. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT-6 Astra (Fast), Macaron V1 Venti or Claude Mythos 5.1?
Macaron V1 Venti is cheaper at $0.825 input / $2.48 output per million tokens (median across 1 API provider). GPT-6 Astra (Fast) costs $20.00 input / $100.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $1.24 per million tokens for Macaron V1 Venti versus $40.00 for GPT-6 Astra (Fast) (32× as much). Claude Mythos 5.1 has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-6 Astra (Fast) has not been scored yet, Macaron V1 Venti has not been scored yet and Claude Mythos 5.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6 Astra (Fast), Macaron V1 Venti and Claude Mythos 5.1 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-6 Astra (Fast) and Macaron V1 Venti have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Claude Mythos 5.1. Maximum output per response: GPT-6 Astra (Fast) up to 128,000, Macaron V1 Venti up to 131,072, Claude Mythos 5.1 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-6 Astra (Fast) accepts text, images and PDFs; Macaron V1 Venti accepts text; Claude Mythos 5.1 accepts text, images and PDFs. GPT-6 Astra (Fast) 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-6 Astra (Fast) and Claude Mythos 5.1 is proprietary.
Which is newer?
GPT-6 Astra (Fast) is the newest, released Sep 4, 2026. Claude Mythos 5.1 came out Sep 1, 2026; Macaron V1 Venti came out Jul 21, 2026. Knowledge cutoff: Claude Mythos 5.1 Jun 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.
