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Data

Data as of October 13, 2026 · How the score is built

Hy4 preview

Decision readingHy4 preview scores 60.9 out of 100 and ranks #48 of 220. This profile shows 30 source-displayable benchmark rows; its strongest eligible category is Coding at #26. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.

Released Aug 28, 2026 — see all recent releases

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

60.9/100

field median 49.9#48 of 220 ranked models

Public

#48of 220

Verified —

Price

Self-hosted; infrastructure cost varies

input median $0.78No comparable first-party hosted token rate

Speed

Not measured

field median 90 tok/sTime to first token not measured

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Coding ranks #26. Particularly well-suited for software development and code generation tasks.

Validate before choosing

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

Source-linked · 30 displayable benchmark rows

Follow model changes

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 #37 of 123Percentile 70thWeight 22%15 benchmarksVerified
54.5
CodingRank #26 of 148Percentile 83rdWeight 20%8 benchmarksVerified
57.1
ReasoningWeight 17%1 benchmarkVerified
Score pending
MultimodalRank Not rankedWeight 12%1 benchmarkVerified
88.3
KnowledgeRank #39 of 180Percentile 79thWeight 12%4 benchmarksVerified
63.6
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%1 benchmarkVerified
Score pending

30 of 670 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

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. Agentic15/15 verified
  2. Coding8/8 verified
  3. Reasoning1/1 verified
  4. Multimodal1/1 verified
  5. Knowledge4/4 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math1/1 verified
Verified sourceProvisionalNot measured

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

  • Agentic70th percentile
  • Coding83rd percentile
  • ReasoningNot eligible
  • MultimodalNot eligible
  • Knowledge79th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#37/123
  2. Coding#26/148
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#39/180
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

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 Opus 5.5 · 89.9%

Gap24.2 behindWeight26% ref. weight
DeepSWEScore64.3%Versus best verified row

Best verified: Muse Wonder Full · 79.0%

Gap14.7 behindWeight15% ref. weight
SWE MultilingualScore82.9%Versus best verified row

Best verified: Claude Opus 5.5 · 93.9%

Gap11 behindWeight5% ref. weight
Terminal-Bench 2.1Score85.4%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap7.4 behindWeightScored in Agentic
NL2RepoScore58.9%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 65.4%

Gap6.5 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: Step 5 Preview · 72.7%

Gap40.8 behindWeightDisplay only
Agentic15 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1Score85.4%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap7.4 behindWeight8% ref. weight
JobBenchScore61.7%Versus best verified row

Best verified: Muse Wonder Full · 75.3%

Gap13.6 behindWeight5% ref. weight
AutomationBenchScore32.1%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 54.8%

Gap22.7 behindWeight5% ref. weight
MCP AtlasScore83.7%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap4.4 behindWeight4% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore55.1%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap32.2 behindWeight3% ref. weight
Toolathlon-VerifiedScore74.1%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap6.5 behindWeight3% ref. weight
Agents' Last ExamScore22.8%Versus best verified row

Best verified: GPT-6 Astra · 59.3%

Gap36.5 behindWeight3% ref. weight
HLE w/ toolsHumanity's Last Exam with toolsScore55.4%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap12.3 behindWeight3% ref. weight
CyberGymScore78.4%Versus best verified row

Best verified: MiMo-V2.6-Flash · 95.1%

Gap16.7 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
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
BankerToolBenchScore78.6%Versus best verified row

Best verified: Hy4 preview · 78.6%

GapBest verifiedWeightDisplay only
CWE-bench v1Score53.0%Versus best verified row

Best verified: GPT-6 Astra · 68.0%

Gap15 behindWeightDisplay only
Reasoning1 row
Reasoning benchmark values, best verified comparison, weight, and source status
CritPtCritical Physics TasksScore16.9%Versus best verified row

Best verified: Muse Wonder Full · 32.9%

Gap16 behindWeightFeeds overall
Multimodal1 row
Multimodal benchmark values, best verified comparison, weight, and source status
OfficeQA ProScore66.2%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap1.5 behindWeightWeighted 25%
Knowledge4 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore55.4%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap9.6 behindWeight44% ref. weight
HLE w/o toolsHumanity's Last Exam without toolsScore43.4%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap21 behindWeight7% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore92.3%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap3.7 behindWeight3% ref. weight
GPQA-DGPQA DiamondScore92.3%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap3.7 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

Bars run 0–100; the dark tick marks the best source-verified value

All 30 rows

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Apr 23, 2026

    Hy3 Preview

    Score 52.0 · Price not listed

  2. Jul 6, 2026

    Hy3

    Not publicly ranked · Price not listed

  3. Aug 28, 2026 · you are here

    Hy4 preview

    Score 60.9 · Price not listed

preview · Preview

Radar

Hy4 preview release history

Full release history

Radar confirmed these at the source. Use Hy4 preview in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

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

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 #48 of 220 on the public leaderboard with a score of 60.86/100. 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. 30 of 670 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Coding at #26, while its lowest eligible position is Knowledge at #39. particularly well-suited for software development and code generation tasks.

Last updated October 13, 2026. Runtime fields remain blank until a sourced snapshot exists.

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

Questions

How does Hy4 preview perform overall in AI benchmarks?

Hy4 preview ranks #48 out of 220 models on the public BenchAlign leaderboard, with a score of 60.86/100. Its evidence status is Estimated, and this profile shows 30 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 ranks #39 out of 180 eligible models for knowledge and understanding, with a public category score of 63.6/100. 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 coding and programming?

Hy4 preview ranks #26 out of 148 eligible models for coding and programming, with a public category score of 57.1/100. 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 #37 out of 123 eligible models for agentic tool use and computer tasks, with a public category score of 54.5/100. 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 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 31 source-displayable rows across 670 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.

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