Hy3

Language Tencent Verified Released Jul 6, 2026
  • In Input modalities: Text Out Output modalities: Text
  • Reasoning· low, high, none
  • Reasoning can be off
  • Tool use
  • Structured output
  • Open weights

Prices

1 offering · prices as listed
Conditions/ 1M tokensInputCache readOutput
Standard ¥1.00¥0.25¥4.00
Batch ¥0.50¥0.125¥2.00

Prices from 腾讯云 TokenHub:模型价格 (opens in a new tab) (checked Oct 30, 2026)

Standard: the price a request with no conditions pays (the headline price elsewhere on the site).

Details

Max input
192K
Licence
Apache 2.0
Family
hy
Aliases
hy3-preview, hy3-202608
Model ID

Not stated on Tencent’s pages: max thinking budget, built-in tools, knowledge cutoff.

Run locally

Weights: tencent/Hy3
  • Parameters 298.8B
  • Active 21B · 192 experts, 8 per token
  • Native precision BF16
  • Layers 80
  • KV cache per token 320 KB
  • Config positions 256K (config.json max_position_embeddings)
  • API context 250K (maker’s API)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Doesn’t fit IQ4_XS (automatic) 8K context
WeightsKV cacheOverheadUsable
Needs
≈ 157.7 GB (weights 147.8 + KV cache 2.5 + overhead 7.4)
Usable
21.6 GB (90% of its memory)
Try
IQ2_XXS runs (needs system memory), but below 4 bits quality drops noticeably
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file556.5 GB≈ 586.9Doesn’t fit—
Q8_0295.7 GB≈ 312.9Doesn’t fit—
FP8maker’s file279.3 GB≈ 295.8Doesn’t fit—
Q6_K228.5 GB≈ 242.5Doesn’t fit—
Q5_K_M197.9 GB≈ 210.3Doesn’t fit—
Q5_0191.3 GB≈ 203.4Doesn’t fit—
Q4_K_M169.0 GB≈ 180.0Doesn’t fit—
Q4_0156.5 GB≈ 166.9Doesn’t fit—
IQ4_XS147.8 GB≈ 157.7Doesn’t fit—
Q3_K_Mquality drops136.0 GB≈ 145.3Doesn’t fit—
IQ3_XXSquality drops106.4 GB≈ 114.3Doesn’t fit—
Q2_Kquality drops104.3 GB≈ 112.1Doesn’t fit—
IQ2_XXSquality drops71.7 GB≈ 77.7Needs system memory 10–15 tok/s—

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): no single listed GPU; unified memory Apple M5 Ultra (64-core GPU) · 256 GB.

Run commands

The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.

Memory to fine-tune
Full≈ 4455.2 GBDoesn’t fit your hardware
LoRA≈ 560.1 GBDoesn’t fit your hardware
QLoRA≈ 160.1 GBDoesn’t fit your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us
  • LMArena Text 1,455

    #50 of 163 listed models · CI 1,449–1,460 · 13,840 votes

  • LMArena Text · Chinese 1,497

    #46 of 161 listed models · CI 1,479–1,516 · 1,065 votes

  • LMArena Text · Coding 1,503

    #49 of 163 listed models · CI 1,493–1,513 · 3,772 votes

  • LMArena Text · Creative writing 1,426

    #52 of 163 listed models · CI 1,414–1,438 · 2,750 votes

  • LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Oct 28, 2026
  • changes we made
  1. 3 new prices on Tencent Cloud TokenHub, China Input (Batch) ¥0.50 · Output (Batch) ¥2.00 · Cache read (Batch) ¥0.125

Sources

Tencent · China · tencent.com

Snapshots, the same family and other models from this provider