Enter opens the highlighted result. Esc closes.

Qwen3.5 397B A17B vs Hy4 preview

Qwen3.5 397B A17B and Hy4 preview cost about the same per output token ($2.34 vs $2.501 per million). Updated October 22, 2026; 3 benchmarks have a result for both.

Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
0
Hy4 previewTencent
Coding
44.3
Overall
No data
Output $/M
$2.501
3
vs boards won of 3 shared

Qwen3.5 397B A17B or Hy4 preview: which to pick

Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.

Pick Qwen3.5 397B A17B for output tokens 1.1x cheaper ($2.34 vs $2.501 per million).

Shared results
3
Qwen3.5 397B A17B only
62
Hy4 preview only
21
Like-for-like categories
1 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Qwen3.5 397B A17B not benchmarked, Hy4 preview 44.3 from 3 benchmarks.
Widest category
Coding, 33.4 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena WebDev: React: Qwen3.5 397B A17B 1388 against Hy4 preview 1653, 35.4 points apart on a 0 to 100 scale.
Output price
Qwen3.5 397B A17B $2.34 against Hy4 preview $2.501 per million output tokens, 1.1x apart.
Context window
Qwen3.5 397B A17B takes 262K tokens, Hy4 preview 1.05M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryQwen3.5 397B A17BBarsHy4 previewTies
Coding03
All shared boards03
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
LMArena WebDev14001631Hy4 preview
Terminal-Bench 4 (Vals AI)Not measured8.1%Only Hy4 preview measured
Vibe Code Bench (Vals AI)Not measured77.5%Only Hy4 preview measured
Code migration (Vals AI)Not measured47.4%Only Hy4 preview measured
ProgramBench (Vals AI)Not measured0.0%Only Hy4 preview measured
IOI (Vals AI)Not measured59.3%Only Hy4 preview measured
Terminal-Bench 2.1 (Vals AI)Not measured55.1%Only Hy4 preview measured
CyberBench (Vals AI)Not measured65.4%Only Hy4 preview measured
SciCode44.8%Not measuredOnly Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)40.9%Not measuredOnly Qwen3.5 397B A17B measured
ALE-Bench621.9Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: coding1464Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: software and IT1463Not measuredOnly Qwen3.5 397B A17B measured
LMArena WebDev: React13881653Hy4 preview
LMArena WebDev: HTML14101620Hy4 preview
Neither model has a result on the other 24 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
AA Intelligence Index21.4Not measuredOnly Qwen3.5 397B A17B measured
Epoch Capabilities Index146.8Not measuredOnly Qwen3.5 397B A17B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
SREBench (Vals AI)Not measured2.3%Only Hy4 preview measured
Finance Agent (Vals AI)Not measured55.1%Only Hy4 preview measured
Tax Agent Bench (Vals AI)Not measured32.6%Only Hy4 preview measured
Legal Research Bench (Vals AI)Not measured45.2%Only Hy4 preview measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured8.8%Only Hy4 preview measured
Excel Modeling Benchmark (Vals AI)Not measured58.1%Only Hy4 preview measured
BioMysteryBench (Vals AI)Not measured69.3%Only Hy4 preview measured
Terminal-Bench-Science (Vals AI)Not measured1.4%Only Hy4 preview measured
τ²-Bench Telecom95.6%Not measuredOnly Qwen3.5 397B A17B measured
APEX-Agents24.9%Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 31 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Reasoning benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
GPQA Diamond (Artificial Analysis run)89.3%Not measuredOnly Qwen3.5 397B A17B measured
Humanity's Last Exam (Artificial Analysis run)29.0%Not measuredOnly Qwen3.5 397B A17B measured
GPQA Diamond (Epoch AI run)86.4%Not measuredOnly Qwen3.5 397B A17B measured
Mystery game puzzles18.0%Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: hard prompts1448Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: expert1462Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: hard prompts in English1450Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: diagrams1277Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: homework1292Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
OTIS Mock AIME88.9%Not measuredOnly Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 331.2%Not measuredOnly Qwen3.5 397B A17B measured
ProofBenchNot measured75.0%Only Hy4 preview measured
LMArena Text: math1453Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: mathematical work1454Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
LegalBench (Vals AI)Not measured83.8%Only Hy4 preview measured
MedCode (Vals AI)Not measured43.3%Only Hy4 preview measured
LMArena Text: science1457Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: medicine and healthcare1455Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: legal and government1441Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: business and finance1435Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
Design Arena: websites1190Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: UI components1160Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: game dev1140Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: data viz1175Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: 3D1160Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: all code categories1179Not measuredOnly Qwen3.5 397B A17B measured
Design Arena: SVG1139Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index32 boards, none shared
General benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
Vals IndexNot measured53.2%Only Hy4 preview measured
Public Benefits Bench (Vals AI)Not measured68.6%Only Hy4 preview measured
MedScribe (Vals AI)Not measured83.6%Only Hy4 preview measured
IFBench78.8%Not measuredOnly Qwen3.5 397B A17B measured
Long context reasoning (AA-LCR)77.3%Not measuredOnly Qwen3.5 397B A17B measured
DTBench87.5%Not measuredOnly Qwen3.5 397B A17B measured
LMCA37.9%Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text1437Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: instruction following1424Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: creative writing1402Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision1262Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: English1443Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: non-English1430Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Chinese1498Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: German1445Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Japanese1429Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Korean1384Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: French1462Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Spanish1441Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Russian1430Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: Polish1447Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: multi-turn1446Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: longer queries1441Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: writing and language1415Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: entertainment and media1399Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: English1268Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: Chinese1314Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: reading text1271Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: humor1262Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: captioning1230Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: recognizing things1265Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: creative writing1260Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.5 397B A17B and Hy4 preview
BenchmarkQwen3.5 397B A17BHy4 previewLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Qwen3.5 397B A17B$0.0016Fits in one request
Hy4 preview$0.0021Fits in one request

Qwen3.5 397B A17B costs less

Repository review

50K input + 3K output tokens

Qwen3.5 397B A17B$0.027Fits in one request
Hy4 preview$0.049Fits in one request

Qwen3.5 397B A17B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5 397B A17B$0.101Fits in one request
Hy4 preview$0.192Fits in one request

Qwen3.5 397B A17B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Qwen3.5 397B A17B and Hy4 preview
SpecificationQwen3.5 397B A17BTencent Hy4 preview
MakerQwenTencent
WeightsOpen weightsOpen weights
ReleasedFebruary 16, 2026August 28, 2026
Context window262K1.05M
Input $/Mtok$0.39$0.834
Output $/Mtok$2.34$2.501
Coding indexNot benchmarked44.3
Independent measurements behind it13
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5 397B A17B better than Hy4 preview for coding?

Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for output tokens 1.1x cheaper ($2.34 vs $2.501 per million).

Which is cheaper, Qwen3.5 397B A17B or Hy4 preview?

Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 per million output tokens; Hy4 preview costs $0.834 and $2.501. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3.5 397B A17B or Hy4 preview?

Hy4 preview, with 1.05M tokens against 262K.

How many benchmarks is the Qwen3.5 397B A17B vs Hy4 preview comparison based on?

3 benchmarks have a result for both models as of October 22, 2026. Qwen3.5 397B A17B's coding index rests on 1 independent benchmark and Hy4 preview's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next