GPT-5.6 Sol vs Hy3
GPT-5.6 Sol leads the LLM Stats Score 54.9 to 43.0. Hy3 is 45.0x cheaper per token.
OpenAI · Tencent · Updated for 2026
Which is better?
GPT-5.6 Sol leads the overall LLM Stats Score 54.9 to 43.0, ranking #3 overall.
In the 6 individual benchmarks reported for both models, GPT-5.6 Sol wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Hy3 is roughly 45.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Sol also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.6 Sol
- overall performance matters — it scores 54.9 and ranks #3 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Hy3
- cost matters — it's about 45.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
45 reported for GPT-5.6 Sol · 31 for Hy3
GPT-5.6 Sol outperforms in 6 benchmarks (BrowseComp, DeepSWE, GPQA, SWE-Bench Pro, Terminal-Bench 2.1, Toolathlon), while Hy3 is better at 0 benchmarks.
GPT-5.6 Sol significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Sol ($5.00/1M tokens) is 35.7x more expensive than Hy3 ($0.14/1M tokens).
For output processing, GPT-5.6 Sol ($30.00/1M tokens) is 51.7x more expensive than Hy3 ($0.58/1M tokens).
In conclusion, GPT-5.6 Sol is more expensive than Hy3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Sol accepts 1,050,000 input tokens compared to Hy3's 262,144 tokens. Hy3 can generate longer responses up to 262,144 tokens, while GPT-5.6 Sol is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.6 Sol supports multimodal inputs, whereas Hy3 does not.
GPT-5.6 Sol can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.6 Sol
Hy3
License
Usage and distribution terms
GPT-5.6 Sol is licensed under a proprietary license, while Hy3 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5.6 Sol was released on 2026-07-09, while Hy3 was released on 2026-07-06.
GPT-5.6 Sol is 0 month newer than Hy3.
Jul 9, 2026
2 months ago
3d newerJul 6, 2026
2 months ago
Knowledge Cutoff
When training data ends
GPT-5.6 Sol has a documented knowledge cutoff of 2026-02-16, while Hy3's cutoff date is not specified.
We can confirm GPT-5.6 Sol's training data extends to 2026-02-16, but cannot make a direct comparison without Hy3's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Sol is available from OpenAI. Hy3 is available from DeepInfra.
GPT-5.6 Sol
Hy3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Sol and Hy3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Sol vs Hy3.