gpt-oss-120b vs Qwen3.8 27B

Updated October 21, 2026. 46 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace gpt-oss-120b Replace Qwen3.8 27B

gpt-oss-120bOpenAI

Coding: 34.5
Overall: 11.6
Output $/M: $0.60

Qwen3.8 27BQwen

Coding: 73.6
Overall: 33.7
Output $/M: $1.35

vs boards won of 46 shared

Decision reading

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 34.5 for gpt-oss-120b.

Pick gpt-oss-120b when output tokens cost 2.3x less, or when a solved task costs $0.51 against $1.26.

Model Agpt-oss-120bOpenAI34.5/1002 independent benchmarks$0.51 per solved task Model BQwen3.8 27BQwen73.6/1002 independent benchmarks$1.26 per solved task

463239

Shared results: 46
gpt-oss-120b only: 32
Qwen3.8 27B only: 39
Like-for-like categories: 7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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.

Coding
Vibe Coding Index, four public coding benchmarks
Qwen3.8 27B
Qwen3.8 27B scores 73.6 against 34.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.8 27B
Qwen3.8 27B leads, 33.7 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 27B
Qwen3.8 27B leads, 45.8 against 3.7.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.8 27B
Qwen3.8 27B leads, 88.9% against 78.5%.
Same board, both measured
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
Qwen3.8 27B
Qwen3.8 27B leads, 84.3% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only gpt-oss-120b has a Design Arena: websites result, 968.
Directional only
Long documents
Listed context window
Qwen3.8 27B
Qwen3.8 27B takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0004, Qwen3.8 27B $0.0007 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
gpt-oss-120b
gpt-oss-120b $0.51, Qwen3.8 27B $1.26.
Published attempt cost and pass rate

At a glance

Coding index: gpt-oss-120b 34.5 from 2 benchmarks, Qwen3.8 27B 73.6 from 2 benchmarks.
Widest category: Agentic work, 42.6 points apart on average over 2 shared benchmarks.
Widest single gap: SWE-bench Verified (Vals AI): gpt-oss-120b 33.6% against Qwen3.8 27B 86.0%, 52.4 points apart on a 0 to 100 scale.
Output price: gpt-oss-120b $0.60 against Qwen3.8 27B $1.35 per million output tokens, 2.3x apart.
Context window: gpt-oss-120b takes 131K tokens, Qwen3.8 27B 1M.

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
Category	gpt-oss-120b	Qwen3.8 27B
Coding	0	6
Intelligence	0	2
Agentic work	0	2
Reasoning	0	6
Math	0	2
Knowledge	1	6
General	0	21
All shared boards	1	45

CodingLike-for-likeFour of these boards feed the Vibe Coding Index06

Coding benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
Aider polyglot	41.8%	Not measured	Only gpt-oss-120b measured
SWE-bench Verified	26.0%	Not measured	Only gpt-oss-120b measured
LiveBench coding	Not measured	86.8%	Only Qwen3.8 27B measured
LMArena WebDev	Not measured	1593	Only Qwen3.8 27B measured
AA Coding Index	30.4	68.1	Qwen3.8 27B
LiveCodeBench (Vals AI)	83.2%	84.0%	Qwen3.8 27B
SWE-bench Verified (Vals AI)	33.6%	86.0%	Qwen3.8 27B
Vibe Code Bench (Vals AI)	Not measured	64.8%	Only Qwen3.8 27B measured
Code migration (Vals AI)	Not measured	14.2%	Only Qwen3.8 27B measured
ProgramBench (Vals AI)	Not measured	0.0%	Only Qwen3.8 27B measured
IOI (Vals AI)	Not measured	39.1%	Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)	Not measured	58.4%	Only Qwen3.8 27B measured
SkillsBench (Vals AI)	Not measured	38.1%	Only Qwen3.8 27B measured
CyberBench (Vals AI)	Not measured	67.8%	Only Qwen3.8 27B measured
LiveCodeBench (Artificial Analysis run)	87.8%	Not measured	Only gpt-oss-120b measured
SciCode	34.0%	46.6%	Qwen3.8 27B
Terminal-Bench Hard (Artificial Analysis run)	23.5%	Not measured	Only gpt-oss-120b measured
Terminal-Bench	18.7%	Not measured	Only gpt-oss-120b measured
WeirdML	48.2%	Not measured	Only gpt-oss-120b measured
ALE-Bench	575.6	Not measured	Only gpt-oss-120b measured
LMArena Text: coding	1379	1483	Qwen3.8 27B
LMArena Text: software and IT	1387	1478	Qwen3.8 27B
LMArena WebDev: React	Not measured	1602	Only Qwen3.8 27B measured
LMArena WebDev: HTML	Not measured	1570	Only Qwen3.8 27B measured
LMArena WebDev: from an image	Not measured	1577	Only Qwen3.8 27B measured
Neither model has a result on the other 13 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
AA Intelligence Index	11.6	33.7	Qwen3.8 27B
Epoch Capabilities Index	139.8	151.7	Qwen3.8 27B

Agentic workLike-for-likePublic boards, shown as published, kept out of the index02

Agentic work benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
AA Agentic Index	3.7	45.8	Qwen3.8 27B
LiveBench research	Not measured	59.4%	Only Qwen3.8 27B measured
LiveBench browser	Not measured	32.0%	Only Qwen3.8 27B measured
LiveBench long agentic	Not measured	27.9%	Only Qwen3.8 27B measured
Finance Agent (Vals AI)	Not measured	48.5%	Only Qwen3.8 27B measured
Tax Agent Bench (Vals AI)	Not measured	30.9%	Only Qwen3.8 27B measured
Legal Research Bench (Vals AI)	Not measured	36.1%	Only Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)	Not measured	59.7%	Only Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)	Not measured	0.0%	Only Qwen3.8 27B measured
τ²-Bench Telecom	65.8%	Not measured	Only gpt-oss-120b measured
APEX-Agents	4.4%	47.5%	Qwen3.8 27B
METR time horizons	56.6%	Not measured	Only gpt-oss-120b measured
Vending-Bench 2	-$22	Not measured	Only gpt-oss-120b measured
Neither model has a result on the other 26 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index06

Reasoning benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
GPQA Diamond	78.5%	88.9%	Qwen3.8 27B
LiveBench reasoning	Not measured	80.0%	Only Qwen3.8 27B measured
MMMU Pro (Vals AI)	Not measured	83.9%	Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)	78.2%	90.5%	Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)	19.6%	33.9%	Qwen3.8 27B
GPQA Diamond (Epoch AI run)	75.8%	Not measured	Only gpt-oss-120b measured
ARC-AGI	Not measured	87.5%	Only Qwen3.8 27B measured
ARC-AGI-2	Not measured	42.4%	Only Qwen3.8 27B measured
SimpleBench	22.1%	Not measured	Only gpt-oss-120b measured
Mystery game puzzles	2.0%	Not measured	Only gpt-oss-120b measured
LMArena Text: hard prompts	1364	1459	Qwen3.8 27B
LMArena Text: expert	1356	1479	Qwen3.8 27B
LMArena Text: hard prompts in English	1368	1461	Qwen3.8 27B
LMArena Vision: diagrams	Not measured	1285	Only Qwen3.8 27B measured
LMArena Vision: homework	Not measured	1295	Only Qwen3.8 27B measured
Neither model has a result on the other 6 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index02

Math benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
AIME	92.6%	Not measured	Only gpt-oss-120b measured
MATH 500 (Vals AI)	94.8%	Not measured	Only gpt-oss-120b measured
MGSM (Vals AI)	92.0%	Not measured	Only gpt-oss-120b measured
AA Math Index	93.4	Not measured	Only gpt-oss-120b measured
AIME 2025 (Artificial Analysis run)	93.4%	Not measured	Only gpt-oss-120b measured
OTIS Mock AIME	88.9%	Not measured	Only gpt-oss-120b measured
ProofBench	Not measured	16.0%	Only Qwen3.8 27B measured
LMArena Text: math	1389	1455	Qwen3.8 27B
LMArena Text: mathematical work	1386	1458	Qwen3.8 27B
Neither model has a result on the other 4 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index16

Knowledge benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
MMLU Pro	79.2%	84.3%	Qwen3.8 27B
LegalBench (Vals AI)	75.9%	82.4%	Qwen3.8 27B
CaseLaw (Vals AI)	48.8%	Not measured	Only gpt-oss-120b measured
CorpFin (Vals AI)	58.2%	Not measured	Only gpt-oss-120b measured
TaxEval (Vals AI)	71.6%	70.8%	gpt-oss-120b
MortgageTax (Vals AI)	Not measured	64.9%	Only Qwen3.8 27B measured
MedQA (Vals AI)	91.4%	Not measured	Only gpt-oss-120b measured
MedCode (Vals AI)	Not measured	28.7%	Only Qwen3.8 27B measured
MMLU Pro (Artificial Analysis run)	80.8%	Not measured	Only gpt-oss-120b measured
LMArena Text: science	1382	1467	Qwen3.8 27B
LMArena Text: medicine and healthcare	1388	1437	Qwen3.8 27B
LMArena Text: legal and government	1355	1447	Qwen3.8 27B
LMArena Text: business and finance	1359	1438	Qwen3.8 27B
Neither model has a result on the other 4 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared

Web design benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
Design Arena: websites	968	Not measured	Only gpt-oss-120b measured
Design Arena: UI components	927	Not measured	Only gpt-oss-120b measured
Design Arena: game dev	992	Not measured	Only gpt-oss-120b measured
Design Arena: data viz	987	Not measured	Only gpt-oss-120b measured
Design Arena: 3D	901	Not measured	Only gpt-oss-120b measured
Design Arena: all code categories	963	Not measured	Only gpt-oss-120b measured
LiveBench design	Not measured	75.9%	Only Qwen3.8 27B measured
Neither model has a result on the other 2 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index021

General benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
LiveBench data analysis	Not measured	76.6%	Only Qwen3.8 27B measured
SAGE (Vals AI)	Not measured	52.4%	Only Qwen3.8 27B measured
MedScribe (Vals AI)	Not measured	83.8%	Only Qwen3.8 27B measured
IFBench	69.0%	Not measured	Only gpt-oss-120b measured
Long context reasoning (AA-LCR)	52.0%	82.0%	Qwen3.8 27B
DTBench	76.3%	88.0%	Qwen3.8 27B
LMCA	22.1%	41.4%	Qwen3.8 27B
Fiction.LiveBench	44.4%	Not measured	Only gpt-oss-120b measured
Creative writing (Lech Mazur)	77.1%	Not measured	Only gpt-oss-120b measured
Surface Evolver Bench	25.0%	45.0%	Qwen3.8 27B
LMArena Text	1366	1440	Qwen3.8 27B
LMArena Text: instruction following	1318	1436	Qwen3.8 27B
LMArena Text: creative writing	1274	1383	Qwen3.8 27B
LMArena Vision	Not measured	1269	Only Qwen3.8 27B measured
LMArena Text: English	1375	1448	Qwen3.8 27B
LMArena Text: non-English	1351	1428	Qwen3.8 27B
LMArena Text: Chinese	1385	1501	Qwen3.8 27B
LMArena Text: German	1353	1443	Qwen3.8 27B
LMArena Text: Japanese	1331	1387	Qwen3.8 27B
LMArena Text: Korean	1282	1384	Qwen3.8 27B
LMArena Text: French	1370	1465	Qwen3.8 27B
LMArena Text: Spanish	1389	1449	Qwen3.8 27B
LMArena Text: Russian	1343	1415	Qwen3.8 27B
LMArena Text: Polish	1353	1439	Qwen3.8 27B
LMArena Text: multi-turn	1340	1440	Qwen3.8 27B
LMArena Text: longer queries	1319	1448	Qwen3.8 27B
LMArena Text: writing and language	1306	1405	Qwen3.8 27B
LMArena Text: entertainment and media	1292	1393	Qwen3.8 27B
LMArena Vision: English	Not measured	1267	Only Qwen3.8 27B measured
LMArena Vision: Chinese	Not measured	1326	Only Qwen3.8 27B measured
LMArena Vision: reading text	Not measured	1281	Only Qwen3.8 27B measured
LMArena Vision: humor	Not measured	1235	Only Qwen3.8 27B measured
LMArena Vision: creative writing	Not measured	1237	Only Qwen3.8 27B measured
Neither model has a result on the other 13 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for gpt-oss-120b and Qwen3.8 27B
Benchmark	gpt-oss-120b	Qwen3.8 27B	Leader
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

gpt-oss-120b$0.0004Fits in one request

Qwen3.8 27B$0.0007Fits in one request

gpt-oss-120b costs less

Repository review

50K input + 3K output tokens

gpt-oss-120b$0.0093Fits in one request

Qwen3.8 27B$0.0060Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

gpt-oss-120b$0.036Exceeds the context window

Qwen3.8 27B$0.021Fits in one request

Qwen3.8 27B 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 gpt-oss-120b and Qwen3.8 27B
Specification	OpenAI gpt-oss-120b	Qwen3.8 27B
Maker	OpenAI	Qwen
Weights	Open weights	Open weights
Released	August 5, 2025	August 14, 2026
Context window	131K	1M
Input $/Mtok	$0.15	$0.04
Output $/Mtok	$0.60	$1.35
Coding index	34.5	73.6
Independent measurements behind it	2	2
Cost per solved task	$0.51	$1.26
Source	OpenRouter listing	OpenRouter listing

Questions

Is gpt-oss-120b better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 34.5 for gpt-oss-120b. Pick gpt-oss-120b when output tokens cost 2.3x less, or when a solved task costs $0.51 against $1.26.

Which is cheaper, gpt-oss-120b or Qwen3.8 27B?

gpt-oss-120b costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.8 27B costs $0.04 and $1.35. Per solved SWE-bench Verified task, gpt-oss-120b costs $0.51 and Qwen3.8 27B $1.26.

Which has the bigger context window, gpt-oss-120b or Qwen3.8 27B?

Qwen3.8 27B, with 1M tokens against 131K.

How many benchmarks is the gpt-oss-120b vs Qwen3.8 27B comparison based on?

46 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/gpt-oss-120b-vs-qwen3-8-27b" title="gpt-oss-120b vs Qwen3.8 27B, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-oss-120b-vs-qwen3-8-27b">LLMBenchmark.ai, gpt-oss-120b vs Qwen3.8 27B</a></p>

Decision reading

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task