Claude Sonnet 5 vs Hy3-preview
Head-to-head specifications
| Metric | Claude Sonnet 5 | Hy3-preview | Difference |
|---|---|---|---|
| Intelligence Index | 53.0 | 29.0 | +82.8% |
| Context window | 1M tokens | 262K tokens | — |
| Blended price ($/1M tokens) | $0.90 | $0.10 | +800.0% |
| Output speed (tokens/s) | 71 | 115 | -38.3% |
| Access | Proprietary API | Open weights | — |
- Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 29.0).
- Hy3-preview is the cheaper model to run at $0.10/1M blended tokens — about 9.0× cheaper.
- Claude Sonnet 5 offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: Claude Sonnet 5 or Hy3-preview?
Claude Sonnet 5 advantages
- General intelligence (+45%)
- Context window (+74%)
Hy3-preview advantages
- Affordability (+89%)
- Output speed (+38%)
Which should you choose?
- Choose the Claude Sonnet 5 if you need the strongest overall reasoning and accuracy.
- Choose the Hy3-preview if you want the lowest cost per token at scale.
- Choose the Claude Sonnet 5 if you work with long documents or large codebases.
Value for money
Hy3-preview offers more intelligence per dollar (4.9× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Claude Sonnet 5 vs Hy3-preview: which should you choose?
Claude Sonnet 5 — Anthropic multimodal model with an Intelligence Index of 53, a 1M-token context window and a blended price of $0.9/1M tokens.
Hy3-preview — Hy3 multimodal model with an Intelligence Index of 29, a 262K-token context window and a blended price of $0.1/1M tokens (open weights).
Claude Sonnet 5 vs Hy3-preview: Claude Sonnet 5 scores higher on the Intelligence Index. Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 29.0). Hy3-preview is the cheaper model to run at $0.10/1M blended tokens — about 9.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Claude Sonnet 5 scores 53.0 versus 29.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Claude Sonnet 5 accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Hy3-preview generates faster (115 vs 71 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Hy3-preview is the cheaper model to run ($0.10 vs $0.90 per 1M tokens). Claude Sonnet 5 is proprietary api and Hy3-preview is open weights. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Claude Sonnet 5 better than the Hy3-preview?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 29.0).
What is the main difference between the Claude Sonnet 5 and the Hy3-preview?
Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 29.0). Hy3-preview is the cheaper model to run at $0.10/1M blended tokens — about 9.0× cheaper.
Which is better value?
Hy3-preview offers more intelligence per dollar (4.9× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Which should I choose?
Choose the Claude Sonnet 5 if you need the strongest overall reasoning and accuracy. Choose the Hy3-preview if you want the lowest cost per token at scale.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.