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ModelCap

Hy4 preview

Official publisher releaseLimited evidenceOpen weights

Tencent·#32 of 351 on the current board·cheaper than #28 GPT-5.6 Terra

Hy4 preview is a language model from Tencent. It ranks #32 of 351 on ModelCap's current board, with a thinly supported Index score of 72.2, partly measured on public benchmarks and partly modeled. Its score range of 63.1–81.4 spans positions #9–#63. It is listed at $0.834 per million input tokens and $2.50 per million output tokens across 4 providers. It reads up to 1M tokens of context, and its weights are openly downloadable.

Figures as of 18 Oct 2026, 04:31 UTC · download the public dataset · methodology

ModelCap Index · Current board
72.2#32
Partly measured on public benchmarks and partly modeled · range 63.1–81.4
Evidence as of 16 Oct 2026, 00:00 UTC
Market Gravity
65.5
Secondary market signal
Input
$0.834
per 1M tokens
Output
$2.50
per 1M tokens
Context
1M
tokens
Providers
4
endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp4Cheapest$0.834$2.501Mfp4100.0%
Novitafp8$0.834$2.501Mfp8100.0%
SiliconFlowfp8$0.834$2.501Mfp8100.0%
Tencentfp8$0.834$2.501Mfp8100.0%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
novita
live
$0.834$2.501M2465 ms36.3 tok/stools · structured
deepinfra
live
$0.834$2.501M2255 ms51.6 tok/stools · structured

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

EffortAgent scoreSource rankSampleSource
Default
Hy4 preview
2.68%
CI 2.0–3.4%
#208.3M obs
85K sessions
LMArena Agent
Match 100%

Reported evaluation leads (11)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.

Dataset / taskMetricValueRevisionProvenance
benchflow/skillsbench
skillsbench_v1_1
—62.9
Unpinned
not published
Reported
Not used in launch estimate
cais/hle
hle
—43.4
Unpinned
not published
Reported
Not used in launch estimate
cais/hle
hle
—55.4
Unpinned
not published
Reported
Not used in launch estimate
datacurve/deep-swe
deep_swe
—64.3
Unpinned
not published
Reported
Not used in launch estimate
harborframework/terminal-bench-2.1
terminalbench_2_1
—85.4
Unpinned
not published
Reported
Not used in launch estimate
hkust-nlp/Toolathlon
toolathlon_verified
—74.1
Unpinned
not published
Reported
Not used in launch estimate
Idavidrein/gpqa
diamond
—92.3
Unpinned
not published
Reported
Not used in launch estimate
IntelligenceLab/Long-Horizon-Terminal-Bench
lhtb2_solved
—15
Unpinned
not published
Reported
Not used in launch estimate
mercor/apex-agents
apex-agents
—37.1
Unpinned
not published
Reported
Not used in launch estimate
ScaleAI/SWE-bench_Pro
SWE_Bench_Pro
—65.7
Unpinned
not published
Reported
Not used in launch estimate
SWE-bench/SWE-bench_Multilingual
swe_bench_multilingual_%_resolved
—82.9
Unpinned
not published
Reported
Not used in launch estimate

Other versions (2)

ModelCap Index · Current board

Methodology
72.2
Partly measured on public benchmarks and partly modeled
Current board
#32 of 351

Limited evidence. Measured on only 1 public benchmark, with limited support, so the score is less certain than a broadly measured one. What this label means

Score range
63.1–81.4
Rank range
#9–#63
Evidence as of
16 Oct 2026, 00:00 UTC
Benchmarks used
LMArena Agent
Technical details
Public rank basis
Measured · blended (measured)
Evidence label
Measured · blended · 8 reported rows against measured corpus ladders (47%); publisher-corpus-prior over 213 held-out anchors (9%); opens above measured predecessor tencent/hy3 on same-family ordering evidence (35%); 1 specialist-board observation at 2.5% support (8%); shrunk 0.9 toward the measured corpus
Index support
2.5% · weak
Identity binding
Exact catalogue product · tencent/tencent/hy4-preview · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata tencent/Hy4-preview@705d81ee51566a186d645b74c974d642ef2828fe (not the evaluation revision)
Index observations used
1
Qualified Index evidence point
72.2
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
72.2 ± 7.1
Independent share
8%
Shrink toward corpus
-0.9
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Corpus ladder · not independent
8 reported rows against measured corpus ladders
77.7 ± 10.447%
Publisher corpus prior · not independent
publisher-corpus-prior over 213 held-out anchors
62.9 ± 23.59%
Family succession · not independent
opens above measured predecessor tencent/hy3 on same-family ordering evidence
70.4 ± 12.035%
Specialist board measurement
1 specialist-board observation at 2.5% support
58.5 ± 25.38%
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
58.5
Evidence status
provisional · 4% mass
General preference
—
Coding
—
Agents & tools
58.5
Reasoning
—
Evidence breadth
5%
Evidence coverage
3%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
72.4
Liquidity (providers × uptime)
70.4
Open reach (HF downloads)
26.1
Surface (context / tools / modalities)
85.0
Freshness
82.4
  • · OpenRouter popularity #5
  • · 4 live providers
  • · HF 30d downloads 22357
  • · Catalogue: context 1048576, reasoning, tools
  • · First seen 2026-08-28

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
83.1
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
100.0
Evaluation provenance
37.9

Not yet published: the base model it derives from, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
65.5
OpenRouter weekly popularity
#5 of 341

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
72.4

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
70.4

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
26.1

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
82.4

Time since first public availability, on a six-month half-life.

Specification

Model ID
tencent/hy4-preview
Context window
1M tokens
Declared output cap
64K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.042 / 1M
First seen on OpenRouter
28 Aug 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
apache-2.0
Pinned revision
705d81ee5156
Parameters
780.0B
Architecture
HYV4ForCausalLM
Model type
hy_v4
Hugging Face downloads (30d)
22K
Downloads (all time)
37K
Likes
508
Repository updated
28 Aug 2026, 14:58 UTC

Benchmark leaderboards featuring Hy4 preview

All leaderboards
Public benchmark boards on which Hy4 preview has a published result
LeaderboardScoreSource rankConfigurationPublished
LMArena Agent leaderboardLMArena2.7%2.0%–3.4%#20 of 52Default16 Oct 2026

Alternatives to Hy4 preview, by the numbers

Ranked neighbours

Models within 3 places of #32 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Tencent models

The same publisher's other current models with a public Index position.

Hy4 preview: common questions

How does Hy4 preview rank among AI models?

Hy4 preview holds ModelCap Index position #32 of 351 ranked language models as of 18 October 2026, with an Index score of 72.2 (interval 63.1–81.4); evidence: measured · blended. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Hy4 preview cost per 1M tokens?

Hy4 preview is listed at $0.834 per 1M input tokens and $2.50 per 1M output tokens as of 18 October 2026 across 4 providers. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $2.92 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Hy4 preview?

Hy4 preview has a published context window of 1M tokens (1,048,576). The snapshot lists a 64,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Hy4 preview open-weight?

Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is tencent/Hy4-preview on Hugging Face.

Which API providers serve Hy4 preview?

4 providers serve Hy4 preview through OpenRouter as of 18 October 2026: DeepInfra, Novita, SiliconFlow and Tencent. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Hy4 preview been evaluated on?

Hy4 preview has published results on 1 public board tracked by ModelCap as of 18 October 2026: LMArena Agent 2.7% (#20 of 52). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was Hy4 preview released?

Hy4 preview first appeared in the catalogue on 28 Aug 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.