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Hy4 preview

Released Aug 28, 2026 see all recent releases

Decision reading
Hy4 preview scores 79.2 out of 100 and ranks #7 of 228. This profile shows 28 source-displayable benchmark rows; its strongest eligible category is Agentic at #9. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.

Data as of August 28, 2026 · How the score is built

Strongest published evidence

Agentic ranks #9. Particularly useful for coding agents, browser research, and computer-use workflows.

Validate before choosing

28 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

79.2/100

field median 58.8

#7 of 228 ranked models

Price

Self-hosted; infrastructure cost varies

input median $1

No comparable first-party hosted token rate

Speed

Not measured

field median 86 tok/s

Time to first token not measured

Context

1Mtokens

field median 256,000

Maximum output length is tracked separately

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Hy4 preview category percentile values

  • Agentic94th percentile
  • Coding93rd percentile
  • ReasoningNot eligible
  • KnowledgeNot eligible
  • MathNot eligible
  • MultilingualNot eligible
  • MultimodalNot eligible
  • Instruction followingNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#9/140
  2. Coding#11/146
  3. ReasoningNot ranked
  4. KnowledgeNot ranked
  5. MathNot ranked
  6. MultilingualNot ranked
  7. MultimodalNot ranked
  8. Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic13/13 verified
  2. Coding8/8 verified
  3. Reasoning1/1 verified
  4. Knowledge4/4 verified
  5. Math1/1 verified
  6. MultilingualNot measured
  7. Multimodal1/1 verified
  8. Inst. FollowingNot measured
Verified sourceProvisionalNot measured

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
tencent/Hy4-previewTencent Hy4 preview model card
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Tencent publishes the BF16 Hy4 preview checkpoint and a separate FP8 quantization under Apache 2.0. The official deployment recipes use the self-hosted hy4-preview model ID with vLLM or SGLang; no first-party hosted token rate is published for this exact checkpoint.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing recordTencent Hy4 preview model card
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #9 of 140Percentile 94thWeight 22%13 benchmarksVerified70.0
CodingRank #11 of 146Percentile 93rdWeight 20%8 benchmarksVerified68.9
ReasoningWeight 17%1 benchmarkVerifiedScore pending
KnowledgeRank Not rankedWeight 12%4 benchmarksVerified82.6
MathWeight 5%1 benchmarkVerifiedScore pending
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank Not rankedWeight 12%1 benchmarkVerified84.0
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding8 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore65.7%Versus best verified row

Best verified: Claude Mythos 5 · 80.3%

Gap14.6 behindWeightWeighted 10%
Terminal-Bench 2.1Terminal-Bench 2.1 (provider run)Score85.4%Versus best verified row

Best verified: GLM-5.3 · 88.2%

Gap2.8 behindWeightDisplay only
SWE MultilingualScore82.9%Versus best verified row

Best verified: Claude Opus 5 · 89.5%

Gap6.6 behindWeightDisplay only
deepSweScore64.3%Versus best verified row

Best verified: GPT-5.6 Sol · 72.7%

Gap8.4 behindWeightDisplay only
NL2RepoScore58.9%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 61.5%

Gap2.6 behindWeightDisplay only
ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch?Score17.5%Versus best verified row

Best verified: Claude Opus 5 · 93.0%

Gap75.5 behindWeightDisplay only
PostTrain BenchScore35.6%Versus best verified row

Best verified: GLM-5.3 · 39.8%

Gap4.2 behindWeightDisplay only
sweMarathonScore31.9%Versus best verified row

Best verified: GLM-5.3 · 42.5%

Gap10.6 behindWeightDisplay only
Agentic13 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1Terminal-Bench 2.1 (provider run)Score85.4%Versus best verified row

Best verified: GLM-5.3 · 88.2%

Gap2.8 behindWeightDisplay only
CyberGymScore78.4%Versus best verified row

Best verified: Fugu Cyber · 86.9%

Gap8.5 behindWeightDisplay only
WideResearchScore83.9%Versus best verified row

Best verified: Hy4 preview · 83.9%

GapBest verifiedWeightDisplay only
DRACOData Research and Analysis with Complex OperationsScore77.2%Versus best verified row

Best verified: Claude Opus 5 · 88.6%

Gap11.4 behindWeightDisplay only
MCP AtlasScore83.7%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap4.4 behindWeightDisplay only
Toolathlon-VerifiedScore74.1%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap6.5 behindWeightDisplay only
APEX-AgentsScore37.1%Versus best verified row

Best verified: Grok 4.6 · 57.5%

Gap20.4 behindWeightDisplay only
skillsBenchScore62.9%Versus best verified row

Best verified: Qwen3.8 Max · 70.2%

Gap7.3 behindWeightDisplay only
JobBenchScore61.7%Versus best verified row

Best verified: Hy4 preview · 61.7%

GapBest verifiedWeightDisplay only
Agents' Last ExamScore22.8%Versus best verified row

Best verified: Qwen3.8 Max · 52.4%

Gap29.6 behindWeightDisplay only
AutomationBenchScore32.1%Versus best verified row

Best verified: GLM-5.3-Flash · 48.8%

Gap16.7 behindWeightDisplay only
BankerToolBenchScore78.6%Versus best verified row

Best verified: Hy4 preview · 78.6%

GapBest verifiedWeightDisplay only
HLE w/ toolsHumanity's Last Exam with toolsScore55.4%Versus best verified row

Best verified: Claude Opus 5 · 64.7%

Gap9.3 behindWeightDisplay only
Reasoning1 row
Reasoning benchmark values, best verified comparison, weight, and source status
CritPtCritical Physics TasksScore16.9%Versus best verified row

Best verified: GLM-5.2 · 20.9%

Gap4 behindWeightDisplay only
Knowledge4 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore55.4%Versus best verified row

Best verified: Claude Opus 5 · 64.7%

Gap9.3 behindWeightWeighted 45%
GPQAGraduate-Level Google-Proof Q&AScore92.3%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap3.2 behindWeightWeighted 7%
GPQA-DGPQA DiamondScore92.3%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap3.2 behindWeightDisplay only
HLE w/o toolsHumanity's Last Exam without toolsScore43.4%Versus best verified row

Best verified: Claude Mythos 5 · 59%

Gap15.6 behindWeightDisplay only
Math1 row
Math benchmark values, best verified comparison, weight, and source status
ApexScore74.2%Versus best verified row

Best verified: Hy4 preview · 74.2%

GapBest verifiedWeightDisplay only
Multimodal1 row
Multimodal benchmark values, best verified comparison, weight, and source status
OfficeQA ProScore66.2%Versus best verified row

Best verified: Claude Opus 5 · 66.9%

Gap0.7 behindWeightWeighted 30%

Lineage

The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Apr 23, 2026

    Hy3 Preview

    Score 43.7 · Price not listed

  2. Jul 6, 2026

    Hy3

    Not publicly ranked · Price not listed

  3. Aug 28, 2026 · you are here

    Hy4 preview

    Score 79.2 · Price not listed

preview · Preview

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Hy4 preview ranks #7 of 228 on the public leaderboard with a score of 79.16/100. It does not yet have enough sourced coverage for a verified position.

Hy4 preview is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Tencent publishes the BF16 Hy4 preview checkpoint and a separate FP8 quantization under Apache 2.0. The official deployment recipes use the self-hosted hy4-preview model ID with vLLM or SGLang; no first-party hosted token rate is published for this exact checkpoint.

Its explicit predecessor is Hy3. 28 of 406 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Agentic at #9, while its lowest eligible position is Coding at #11. particularly useful for coding agents, browser research, and computer-use workflows.

Radar

Hy4 preview release history

Full release history

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Frequently asked questions

How does Hy4 preview perform overall in AI benchmarks?

Hy4 preview ranks #7 out of 228 models on the public BenchAlign leaderboard, with a score of 79.16/100. Its evidence status is Estimated, and this profile shows 28 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Hy4 preview good for knowledge and understanding?

Hy4 preview has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Hy4 preview good for coding and programming?

Hy4 preview ranks #11 out of 146 eligible models for coding and programming, with a public category score of 68.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Hy4 preview good for mathematics?

Hy4 preview has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Hy4 preview good for reasoning and logic?

Hy4 preview has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Hy4 preview good for agentic tool use and computer tasks?

Hy4 preview ranks #9 out of 140 eligible models for agentic tool use and computer tasks, with a public category score of 70/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Hy4 preview good for multimodal and grounded tasks?

Hy4 preview has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Hy4 preview open source?

Hy4 preview is an open-weight model from Tencent. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Does Hy4 preview have full benchmark coverage on BenchLM?

No. Hy4 preview currently has 29 source-displayable rows across 406 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Hy4 preview?

Hy4 preview has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

Compare Hy4 preview with every tracked model399 comparisons

Last updated August 28, 2026. Runtime fields remain blank until a sourced snapshot exists.

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