GPT-6 Astra (Fast) vs Hy4 preview vs Macaron V1 Venti
Too close to call on our weighted score (Macaron V1 Venti 44, Hy4 preview 44, GPT-6 Astra (Fast) 33). The right pick depends on what you value most.
OpenAIGPT-6 Astra (Fast)
33/100- ECI—
- Price$20.00 / $100.00
- Context1.05M
TencentHy4 preview
44/100- ECI—
- Price$0.834 / $2.50
- Context1.02M
Mindlab
Macaron V1 Venti
44/100- ECI—
- Price$0.825 / $2.48
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (Macaron V1 Venti 44/100, Hy4 preview 44/100, GPT-6 Astra (Fast) 33/100), so choose by what matters most for your work: Macaron V1 Venti 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 · Hy4 preview $1.25 · GPT-6 Astra (Fast) $40.00 per 1M tokens (3:1 blend)
- Longest contextGPT-6 Astra (Fast) and Macaron V1 VentiGPT-6 Astra (Fast) 1,050,000 · Macaron V1 Venti 1,048,576 · Hy4 preview 1,024,000 tokens
- Widest inputsGPT-6 Astra (Fast)GPT-6 Astra (Fast): Text, Images, PDFs · Hy4 preview: Text · Macaron V1 Venti: Text
- Self-hostingHy4 preview and Macaron V1 VentiPublishes downloadable weights (MIT)
| Measure | Weight | GPT-6 Astra (Fast) | Hy4 preview | Macaron V1 Venti |
|---|---|---|---|---|
| Price | 50% | 0 | 43 | 44 |
| Inputs & features | 30% | 70 | 35 | 35 |
| Context window | 20% | 61 | 60 | 61 |
| Overall | 100% | 33/100 | 44/100 | 44/100 |
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-6 Astra (Fast)OpenAI | Hy4 previewTencent | Macaron V1 VentiMindlab |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $20.00 | $0.834 | $0.825 (best) |
| Output | $100.00 | $2.50 | $2.48 (best) |
| Cached input | — | $0.042 | — |
| Blended (3:1) | $40.00 | $1.25 | $1.24 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Tencent TokenHub API | Median of 1 providers |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,024,000 tokens | 1,048,576 tokens |
| Max output | 128,000 tokens | 64,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeshigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | OpenMIT |
| API model ID | — | hy4-preview | — |
| API providers | 1 | 17 (best) | 1 |
| Released | Sep 4, 2026 | Aug 28, 2026 | Jul 21, 2026 |
| Knowledge cutoff | — | — | — |
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
- Hy4 preview$13.34
- Macaron V1 Venti$13.20
Which should you choose?
Which is better: GPT-6 Astra (Fast), Hy4 preview or Macaron V1 Venti?
It is close. Our weighted score puts them within a point (Macaron V1 Venti 44/100, Hy4 preview 44/100, GPT-6 Astra (Fast) 33/100), so choose by what matters most for your work: Macaron V1 Venti 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-6 Astra (Fast), Hy4 preview or Macaron V1 Venti?
Macaron V1 Venti is cheaper at $0.825 input / $2.48 output per million tokens (median across 1 API provider). Hy4 preview costs $0.834 input / $2.50 output per million tokens (official Tencent TokenHub API price); 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 $1.25 for Hy4 preview (1× as much) and $40.00 for GPT-6 Astra (Fast) (32× as much).
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, Hy4 preview has not been scored yet and Macaron V1 Venti has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6 Astra (Fast), Hy4 preview and Macaron V1 Venti 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 1,024,000 for Hy4 preview. Maximum output per response: GPT-6 Astra (Fast) up to 128,000, Hy4 preview up to 64,000, Macaron V1 Venti up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GPT-6 Astra (Fast) accepts text, images and PDFs; Hy4 preview accepts text; Macaron V1 Venti accepts text. GPT-6 Astra (Fast) handles the widest range of inputs.
Are any of these open source?
Hy4 preview and Macaron V1 Venti publishes its weights (MIT) and can be self-hosted; GPT-6 Astra (Fast) is proprietary.
Which is newer?
GPT-6 Astra (Fast) is the newest, released Sep 4, 2026. Hy4 preview came out Aug 28, 2026; Macaron V1 Venti came out Jul 21, 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.
