Mistral Large 4 vs Qwen3.8 27B

Qwen3.8 27B leads Mistral Large 4 on coding, 74.2 to 56.4 on the Vibe Coding Index, and Qwen3.8 27B costs 1.6x less per output token ($2.55 vs $4.18 per million). Updated October 22, 2026; 57 benchmarks have a result for both.

Replace Mistral Large 4 Replace Qwen3.8 27B

Mistral Large 4Mistral AI

Coding: 56.4
Overall: 54.6
Output $/M: $4.18

Qwen3.8 27BQwen

Coding: 74.2
Overall: 59.6
Output $/M: $2.55

vs boards won of 57 shared

Mistral Large 4 or Qwen3.8 27B: which to pick

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 56.4 for Mistral Large 4, though on 4 benchmarks against 5.

Pick Mistral Large 4 for a larger context window (1.05M against 1M tokens) and work measured by Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.

Model AMistral Large 4Mistral AI56.4/1005 independent benchmarksNo cost per solved task Model BQwen3.8 27BQwen74.2/1004 independent benchmarks$1.26 per solved task

572428

Shared results: 57
Mistral Large 4 only: 24
Qwen3.8 27B only: 28
Like-for-like categories: 8 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.

Coding
Vibe Coding Index, six public coding benchmarks
Qwen3.8 27B
Qwen3.8 27B scores 74.2 against 56.4.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 33.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 27B has a AA Agentic Index result, 45.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 27B has a GPQA Diamond result, 88.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 27B has a MMLU Pro result, 84.3%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 27B
Mistral Large 4 $0.0034, Qwen3.8 27B $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 27B has the number, $1.26.
Directional only

At a glance

Coding index: Mistral Large 4 56.4 from 5 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
Widest category: Agentic work, 12.3 points apart on average over 7 shared benchmarks.
Widest single gap: LiveBench research: Mistral Large 4 28.1% against Qwen3.8 27B 59.4%, 31.3 points apart on a 0 to 100 scale.
Output price: Mistral Large 4 $4.18 against Qwen3.8 27B $2.55 per million output tokens, 1.6x apart.
Context window: Mistral Large 4 takes 1.05M 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	Mistral Large 4	Qwen3.8 27B
Coding	4	6
Intelligence	1	1
Agentic work	1	6
Reasoning	3	3
Math	2	1
Knowledge	2	3
Web design	0	1
General	8	15
All shared boards	21	36

CodingLike-for-likeSix of these boards feed the Vibe Coding Index46

Coding benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
LiveBench coding	60.0%	86.8%	Qwen3.8 27B
LMArena WebDev	1543	1593	Qwen3.8 27B
AA Coding Index	Not measured	68.1	Only Qwen3.8 27B measured
LiveCodeBench (Vals AI)	Not measured	84.0%	Only Qwen3.8 27B measured
SWE-bench Verified (Vals AI)	Not measured	86.0%	Only Qwen3.8 27B measured
Terminal-Bench 4 (Vals AI)	27.8%	Not measured	Only Mistral Large 4 measured
Vibe Code Bench (Vals AI)	78.4%	64.8%	Mistral Large 4
Code migration (Vals AI)	30.6%	14.2%	Mistral Large 4
ProgramBench (Vals AI)	Not measured	0.0%	Only Qwen3.8 27B measured
IOI (Vals AI)	45.3%	39.1%	Mistral Large 4
Terminal-Bench 2.1 (Vals AI)	Not measured	58.4%	Only Qwen3.8 27B measured
SWE-bench Multimodal (Vals AI)	33.1%	Not measured	Only Mistral Large 4 measured
Vibe Code Bench 1-100 (Vals AI)	14.3%	Not measured	Only Mistral Large 4 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
SciCode	54.2%	46.6%	Mistral Large 4
FrontierCode	39.4%	Not measured	Only Mistral Large 4 measured
ALE-Bench	1213.2	Not measured	Only Mistral Large 4 measured
LMArena Text: coding	1478	1483	Qwen3.8 27B
LMArena Text: software and IT	1467	1478	Qwen3.8 27B
LMArena WebDev: React	1559	1602	Qwen3.8 27B
LMArena WebDev: HTML	1487	1570	Qwen3.8 27B
LMArena WebDev: from an image	Not measured	1577	Only Qwen3.8 27B measured
Neither model has a result on the other 16 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11

Intelligence benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
AA Intelligence Index	38.4	33.7	Mistral Large 4
Epoch Capabilities Index	150.0	151.7	Qwen3.8 27B

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

Agentic work benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
AA Agentic Index	Not measured	45.8	Only Qwen3.8 27B measured
LiveBench research	28.1%	59.4%	Qwen3.8 27B
LiveBench browser	8.0%	32.0%	Qwen3.8 27B
LiveBench long agentic	11.8%	27.9%	Qwen3.8 27B
Finance Agent (Vals AI)	54.7%	48.5%	Mistral Large 4
Tax Agent Bench (Vals AI)	30.4%	30.9%	Qwen3.8 27B
Legal Research Bench (Vals AI)	31.7%	36.1%	Qwen3.8 27B
Harvey's Legal Agent Benchmark (Vals AI)	17.5%	Not measured	Only Mistral Large 4 measured
Excel Modeling Benchmark (Vals AI)	56.2%	59.7%	Qwen3.8 27B
BioMysteryBench (Vals AI)	67.0%	Not measured	Only Mistral Large 4 measured
Terminal-Bench-Science (Vals AI)	Not measured	0.0%	Only Qwen3.8 27B measured
APEX-Agents	Not measured	47.5%	Only Qwen3.8 27B measured
Neither model has a result on the other 29 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index33

Reasoning benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
GPQA Diamond	Not measured	88.9%	Only Qwen3.8 27B measured
LiveBench reasoning	83.9%	80.0%	Mistral Large 4
MysteryMechanism (Vals AI)	12.2%	Not measured	Only Mistral Large 4 measured
MMMU Pro (Vals AI)	Not measured	83.9%	Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)	Not measured	90.5%	Only Qwen3.8 27B measured
Humanity's Last Exam (Artificial Analysis run)	35.0%	33.9%	Mistral Large 4
GPQA Diamond (Epoch AI run)	88.1%	Not measured	Only Mistral Large 4 measured
ARC-AGI	Not measured	87.5%	Only Qwen3.8 27B measured
ARC-AGI-2	Not measured	42.4%	Only Qwen3.8 27B measured
Chess puzzles	33.0%	Not measured	Only Mistral Large 4 measured
Mystery game puzzles	17.0%	Not measured	Only Mistral Large 4 measured
LMArena Text: hard prompts	1444	1459	Qwen3.8 27B
LMArena Text: expert	1444	1479	Qwen3.8 27B
LMArena Text: hard prompts in English	1442	1461	Qwen3.8 27B
LMArena Vision: diagrams	1288	1285	Mistral Large 4
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 index21

Math benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
OTIS Mock AIME	98.3%	Not measured	Only Mistral Large 4 measured
FrontierMath, tiers 1 to 3	58.6%	Not measured	Only Mistral Large 4 measured
FrontierMath, tier 4	26.8%	Not measured	Only Mistral Large 4 measured
ProofBench	10.0%	16.0%	Qwen3.8 27B
LMArena Text: math	1469	1455	Mistral Large 4
LMArena Text: mathematical work	1462	1458	Mistral Large 4
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index23

Knowledge benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
MMLU Pro	Not measured	84.3%	Only Qwen3.8 27B measured
LegalBench (Vals AI)	Not measured	82.4%	Only Qwen3.8 27B measured
TaxEval (Vals AI)	Not measured	70.8%	Only Qwen3.8 27B measured
MortgageTax (Vals AI)	Not measured	64.9%	Only Qwen3.8 27B measured
MedCode (Vals AI)	40.7%	28.7%	Mistral Large 4
SimpleQA Verified	20.0%	Not measured	Only Mistral Large 4 measured
LMArena Text: science	1448	1467	Qwen3.8 27B
LMArena Text: medicine and healthcare	1433	1437	Qwen3.8 27B
LMArena Text: legal and government	1425	1447	Qwen3.8 27B
LMArena Text: business and finance	1439	1438	Mistral Large 4
Neither model has a result on the other 8 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index01

Web design benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
Design Arena: websites	1257	Not measured	Only Mistral Large 4 measured
Design Arena: UI components	1272	Not measured	Only Mistral Large 4 measured
Design Arena: game dev	1225	Not measured	Only Mistral Large 4 measured
Design Arena: data viz	1275	Not measured	Only Mistral Large 4 measured
Design Arena: 3D	1252	Not measured	Only Mistral Large 4 measured
Design Arena: all code categories	1259	Not measured	Only Mistral Large 4 measured
Design Arena: SVG	1232	Not measured	Only Mistral Large 4 measured
Design Arena: ASCII art	1202	Not measured	Only Mistral Large 4 measured
LiveBench design	65.6%	75.9%	Qwen3.8 27B

GeneralLike-for-likePublic boards, shown as published, kept out of the index815

General benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	Qwen3.8 27B	Leader
LiveBench data analysis	76.5%	76.6%	Qwen3.8 27B
SAGE (Vals AI)	Not measured	52.4%	Only Qwen3.8 27B measured
MedScribe (Vals AI)	80.4%	83.8%	Qwen3.8 27B
Long context reasoning (AA-LCR)	81.3%	82.0%	Qwen3.8 27B
DTBench	88.2%	88.0%	Mistral Large 4
LMCA	35.8%	41.4%	Qwen3.8 27B
Surface Evolver Bench	28.1%	45.0%	Qwen3.8 27B
Furniture assembly	20.8%	Not measured	Only Mistral Large 4 measured
LMArena Text	1431	1440	Qwen3.8 27B
LMArena Text: instruction following	1422	1436	Qwen3.8 27B
LMArena Text: creative writing	1363	1383	Qwen3.8 27B
LMArena Vision	1272	1269	Mistral Large 4
LMArena Text: English	1433	1448	Qwen3.8 27B
LMArena Text: non-English	1422	1428	Qwen3.8 27B
LMArena Text: Chinese	1492	1501	Qwen3.8 27B
LMArena Text: German	Not measured	1443	Only Qwen3.8 27B measured
LMArena Text: Japanese	1415	1387	Mistral Large 4
LMArena Text: Korean	Not measured	1384	Only Qwen3.8 27B measured
LMArena Text: French	1492	1465	Mistral Large 4
LMArena Text: Spanish	1455	1449	Mistral Large 4
LMArena Text: Russian	1417	1415	Mistral Large 4
LMArena Text: Polish	Not measured	1439	Only Qwen3.8 27B measured
LMArena Text: multi-turn	1435	1440	Qwen3.8 27B
LMArena Text: longer queries	1428	1448	Qwen3.8 27B
LMArena Text: writing and language	1386	1405	Qwen3.8 27B
LMArena Text: entertainment and media	1378	1393	Qwen3.8 27B
LMArena Vision: English	1283	1267	Mistral Large 4
LMArena Vision: Chinese	Not measured	1326	Only Qwen3.8 27B measured
LMArena Vision: reading text	1284	1281	Mistral Large 4
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 15 boards here

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

Image generation benchmarks for Mistral Large 4 and Qwen3.8 27B
Benchmark	Mistral Large 4	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

Mistral Large 4$0.0034Fits in one request

Qwen3.8 27B$0.0017Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

Mistral Large 4$0.081Fits in one request

Qwen3.8 27B$0.029Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

Mistral Large 4$0.314Fits in one request

Qwen3.8 27B$0.111Fits 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 Mistral Large 4 and Qwen3.8 27B
Specification	Mistral Large 4	Qwen3.8 27B
Maker	Mistral AI	Qwen
Weights	No public weights listed	Open weights
Released	October 6, 2026	August 14, 2026
Context window	1.05M	1M
Input $/Mtok	$1.36	$0.425
Output $/Mtok	$4.18	$2.55
Coding index	56.4	74.2
Independent measurements behind it	5	4
Cost per solved task	Not computable	$1.26
Source	OpenRouter listing	OpenRouter listing

Questions

Is Mistral Large 4 better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 56.4 for Mistral Large 4, though on 4 benchmarks against 5. Pick Mistral Large 4 for a larger context window (1.05M against 1M tokens) and work measured by Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.

Which is cheaper, Mistral Large 4 or Qwen3.8 27B?

Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Cost per solved task is known for Qwen3.8 27B only.

Which has the bigger context window, Mistral Large 4 or Qwen3.8 27B?

Mistral Large 4, with 1.05M tokens against 1M.

How many benchmarks is the Mistral Large 4 vs Qwen3.8 27B comparison based on?

57 benchmarks have a result for both models as of October 22, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.

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Mistral Large 4 or Qwen3.8 27B: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next