โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Hy3 vs Llama 3.1 405B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Hy3 and Llama 3.1 405B.

Tencent

Hy3

Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort:...

View Full Specs
Meta

Llama 3.1 405B

Llama 3.1 405B is Meta's largest open-weight language model and one of the most capable openly available models in the world. With 405 billion parameters, it achieves performance competitive with GPT-4 and Claude Opus across benchmarks spanning general knowledge, mathematics, coding, and multilingual tasks. Llama 3.1 405B is released under Meta's custom commercial license, supporting broad use cases including deployment via major cloud providers (AWS, GCP, Azure) and self-hosted inference with multi-GPU configurations.

View Full Specs

Technical Specifications

SpecificationHy3Llama 3.1 405B
ProviderTencentMeta
Context Window262,144 tokens131,072 tokens
Agent SuitabilityN/A90/100
Time to First Token (TTFT)N/A550 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-07-062024-07-23

API Pricing Comparison

Input Price per Million Tokens

Hy3

$0.20

Llama 3.1 405B

$0.80

Output Price per Million Tokens

Hy3

$0.80

Llama 3.1 405B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

Hy3 Quirks & Gotchas

No developer gotchas reported.

Llama 3.1 405B Quirks & Gotchas

  • โ–ธMassive model โ€” requires 8ร— A100 80GB for FP16 inference
  • โ–ธAvailable via Together AI, Fireworks, and Bedrock as managed API