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Qwen3.8 27B vs Hy-MT2-7B

Hy-MT2-7B costs 8.6x less per output token than Qwen3.8 27B ($0.295 vs $2.55 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Qwen3.8 27BQwen
Coding
74.2
Overall
59.6
Output $/M
$2.55
Hy-MT2-7BTencent
Coding
No data
Overall
No data
Output $/M
$0.295
vs $2.55 vs $0.295 per 1M output tokens. Hy-MT2-7B is 8.6x cheaper.

Qwen3.8 27B or Hy-MT2-7B: which to pick

Only Qwen3.8 27B has a coding score, 74.2 on the Vibe Coding Index; Hy-MT2-7B has none, so the two cannot be ranked on coding.

Pick Hy-MT2-7B for output tokens 8.6x cheaper ($0.295 vs $2.55 per million).

No benchmark has tested both yet. Qwen3.8 27B has results on LiveBench coding, LMArena WebDev and AA Coding Index; Hy-MT2-7B has none yet. Compare them on price and context instead.

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
Qwen3.8 27B 74.2 from 4 benchmarks, Hy-MT2-7B not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Qwen3.8 27B $2.55 against Hy-MT2-7B $0.295 per million output tokens, 8.6x apart.
Context window
Qwen3.8 27B takes 1M tokens, Hy-MT2-7B 8K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards measured
Coding benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
LiveBench coding86.8%Not measuredOnly Qwen3.8 27B measured
LMArena WebDev1593Not measuredOnly Qwen3.8 27B measured
AA Coding Index68.1Not measuredOnly Qwen3.8 27B measured
LiveCodeBench (Vals AI)84.0%Not measuredOnly Qwen3.8 27B measured
SWE-bench Verified (Vals AI)86.0%Not measuredOnly Qwen3.8 27B measured
Vibe Code Bench (Vals AI)64.8%Not measuredOnly Qwen3.8 27B measured
Code migration (Vals AI)14.2%Not measuredOnly Qwen3.8 27B measured
ProgramBench (Vals AI)0.0%Not measuredOnly Qwen3.8 27B measured
IOI (Vals AI)39.1%Not measuredOnly Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)58.4%Not measuredOnly Qwen3.8 27B measured
SkillsBench (Vals AI)38.1%Not measuredOnly Qwen3.8 27B measured
CyberBench (Vals AI)67.8%Not measuredOnly Qwen3.8 27B measured
SciCode46.6%Not measuredOnly Qwen3.8 27B measured
LMArena Text: coding1483Not measuredOnly Qwen3.8 27B measured
LMArena Text: software and IT1478Not measuredOnly Qwen3.8 27B measured
LMArena WebDev: React1602Not measuredOnly Qwen3.8 27B measured
LMArena WebDev: HTML1570Not measuredOnly Qwen3.8 27B measured
LMArena WebDev: from an image1577Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 21 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
AA Intelligence Index33.7Not measuredOnly Qwen3.8 27B measured
Epoch Capabilities Index151.7Not measuredOnly Qwen3.8 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
Agentic work benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
AA Agentic Index45.8Not measuredOnly Qwen3.8 27B measured
LiveBench research59.4%Not measuredOnly Qwen3.8 27B measured
LiveBench browser32.0%Not measuredOnly Qwen3.8 27B measured
LiveBench long agentic27.9%Not measuredOnly Qwen3.8 27B measured
Finance Agent (Vals AI)48.5%Not measuredOnly Qwen3.8 27B measured
Tax Agent Bench (Vals AI)30.9%Not measuredOnly Qwen3.8 27B measured
Legal Research Bench (Vals AI)36.1%Not measuredOnly Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)59.7%Not measuredOnly Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)0.0%Not measuredOnly Qwen3.8 27B measured
APEX-Agents47.5%Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 31 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
Reasoning benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
GPQA Diamond88.9%Not measuredOnly Qwen3.8 27B measured
LiveBench reasoning80.0%Not measuredOnly Qwen3.8 27B measured
MMMU Pro (Vals AI)83.9%Not measuredOnly Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)90.5%Not measuredOnly Qwen3.8 27B measured
Humanity's Last Exam (Artificial Analysis run)33.9%Not measuredOnly Qwen3.8 27B measured
ARC-AGI87.5%Not measuredOnly Qwen3.8 27B measured
ARC-AGI-242.4%Not measuredOnly Qwen3.8 27B measured
LMArena Text: hard prompts1459Not measuredOnly Qwen3.8 27B measured
LMArena Text: expert1479Not measuredOnly Qwen3.8 27B measured
LMArena Text: hard prompts in English1461Not measuredOnly Qwen3.8 27B measured
LMArena Vision: diagrams1285Not measuredOnly Qwen3.8 27B measured
LMArena Vision: homework1295Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Math benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
ProofBench16.0%Not measuredOnly Qwen3.8 27B measured
LMArena Text: math1455Not measuredOnly Qwen3.8 27B measured
LMArena Text: mathematical work1458Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
Knowledge benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
MMLU Pro84.3%Not measuredOnly Qwen3.8 27B measured
LegalBench (Vals AI)82.4%Not measuredOnly Qwen3.8 27B measured
TaxEval (Vals AI)70.8%Not measuredOnly Qwen3.8 27B measured
MortgageTax (Vals AI)64.9%Not measuredOnly Qwen3.8 27B measured
MedCode (Vals AI)28.7%Not measuredOnly Qwen3.8 27B measured
LMArena Text: science1467Not measuredOnly Qwen3.8 27B measured
LMArena Text: medicine and healthcare1437Not measuredOnly Qwen3.8 27B measured
LMArena Text: legal and government1447Not measuredOnly Qwen3.8 27B measured
LMArena Text: business and finance1438Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Web design benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
LiveBench design75.9%Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 8 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards measured
General benchmarks for Qwen3.8 27B and Hy-MT2-7B
BenchmarkQwen3.8 27BHy-MT2-7BLeader
LiveBench data analysis76.6%Not measuredOnly Qwen3.8 27B measured
SAGE (Vals AI)52.4%Not measuredOnly Qwen3.8 27B measured
MedScribe (Vals AI)83.8%Not measuredOnly Qwen3.8 27B measured
Long context reasoning (AA-LCR)82.0%Not measuredOnly Qwen3.8 27B measured
DTBench88.0%Not measuredOnly Qwen3.8 27B measured
LMCA41.4%Not measuredOnly Qwen3.8 27B measured
Surface Evolver Bench45.0%Not measuredOnly Qwen3.8 27B measured
LMArena Text1440Not measuredOnly Qwen3.8 27B measured
LMArena Text: instruction following1436Not measuredOnly Qwen3.8 27B measured
LMArena Text: creative writing1383Not measuredOnly Qwen3.8 27B measured
LMArena Vision1269Not measuredOnly Qwen3.8 27B measured
LMArena Text: English1448Not measuredOnly Qwen3.8 27B measured
LMArena Text: non-English1428Not measuredOnly Qwen3.8 27B measured
LMArena Text: Chinese1501Not measuredOnly Qwen3.8 27B measured
LMArena Text: German1443Not measuredOnly Qwen3.8 27B measured
LMArena Text: Japanese1387Not measuredOnly Qwen3.8 27B measured
LMArena Text: Korean1384Not measuredOnly Qwen3.8 27B measured
LMArena Text: French1465Not measuredOnly Qwen3.8 27B measured
LMArena Text: Spanish1449Not measuredOnly Qwen3.8 27B measured
LMArena Text: Russian1415Not measuredOnly Qwen3.8 27B measured
LMArena Text: Polish1439Not measuredOnly Qwen3.8 27B measured
LMArena Text: multi-turn1440Not measuredOnly Qwen3.8 27B measured
LMArena Text: longer queries1448Not measuredOnly Qwen3.8 27B measured
LMArena Text: writing and language1405Not measuredOnly Qwen3.8 27B measured
LMArena Text: entertainment and media1393Not measuredOnly Qwen3.8 27B measured
LMArena Vision: English1267Not measuredOnly Qwen3.8 27B measured
LMArena Vision: Chinese1326Not measuredOnly Qwen3.8 27B measured
LMArena Vision: reading text1281Not measuredOnly Qwen3.8 27B measured
LMArena Vision: humor1235Not measuredOnly Qwen3.8 27B measured
LMArena Vision: creative writing1237Not measuredOnly Qwen3.8 27B measured
Neither model has a result on the other 16 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

Qwen3.8 27B$0.0017Fits in one request
Hy-MT2-7B$0.0002Fits in one request

Hy-MT2-7B costs less

Repository review

50K input + 3K output tokens

Qwen3.8 27B$0.029Fits in one request
Hy-MT2-7B$0.0046Exceeds the context window

Hy-MT2-7B costs less

Agent loop

200K input + 10K output tokens

Qwen3.8 27B$0.111Fits in one request
Hy-MT2-7B$0.018Exceeds the context window

Hy-MT2-7B 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 Qwen3.8 27B and Hy-MT2-7B
SpecificationQwen3.8 27BTencent Hy-MT2-7B
MakerQwenTencent
WeightsOpen weightsOpen weights
ReleasedAugust 14, 2026August 19, 2026
Context window1M8K
Input $/Mtok$0.425$0.074
Output $/Mtok$2.55$0.295
Coding index74.2Not benchmarked
Independent measurements behind it40
Cost per solved task$1.26Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.8 27B better than Hy-MT2-7B for coding?

Only Qwen3.8 27B has a coding score, 74.2 on the Vibe Coding Index; Hy-MT2-7B has none, so the two cannot be ranked on coding. Pick Hy-MT2-7B for output tokens 8.6x cheaper ($0.295 vs $2.55 per million).

Which is cheaper, Qwen3.8 27B or Hy-MT2-7B?

Qwen3.8 27B costs $0.425 per million input tokens and $2.55 per million output tokens; Hy-MT2-7B costs $0.074 and $0.295. Cost per solved task is known for Qwen3.8 27B only.

Which has the bigger context window, Qwen3.8 27B or Hy-MT2-7B?

Qwen3.8 27B, with 1M tokens against 8K.

Has any benchmark tested both Qwen3.8 27B and Hy-MT2-7B?

No benchmark has tested both yet. Qwen3.8 27B has results on LiveBench coding, LMArena WebDev and AA Coding Index; Hy-MT2-7B has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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