Gemini 3.8 Flash vs MiniMax M2.5

Updated October 21, 2026. 55 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 3.8 Flash Replace MiniMax M2.5

Gemini 3.8 FlashGoogle

Coding: 70.5
Overall: 40.9
Output $/M: $4.125

MiniMax M2.5MiniMax

Coding: 59.4
Overall: 22.8
Output $/M: $0.95

vs boards won of 55 shared

Decision reading

Pick Gemini 3.8 Flash for coding: it scores 70.5 on the Vibe Coding Index against 59.4 for MiniMax M2.5.

Pick MiniMax M2.5 when output tokens cost 4.3x less, or when a solved task costs $0.62 against $2.74.

Model AGemini 3.8 FlashGoogle70.5/1002 independent benchmarks$2.74 per solved task Model BMiniMax M2.5MiniMax59.4/1002 independent benchmarks$0.62 per solved task

557112

Shared results: 55
Gemini 3.8 Flash only: 71
MiniMax M2.5 only: 12
Like-for-like categories: 8 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
Gemini 3.8 Flash
Gemini 3.8 Flash scores 70.5 against 59.4.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 22.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 3.8 Flash has a AA Agentic Index result, 40.2.
Directional only
Reasoning
GPQA Diamond
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 94.4% against 82.1%.
Same board, both measured
Math
AIME
No call
Only MiniMax M2.5 has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 90.2% against 80.1%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1301 against 1222.
Same board, both measured
General
Vals Index
No call
Only Gemini 3.8 Flash has a Vals Index result, 56.0%.
Directional only
Long documents
Listed context window
Gemini 3.8 Flash
Gemini 3.8 Flash takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.5
Gemini 3.8 Flash $0.0029, MiniMax M2.5 $0.0007 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2.5
Gemini 3.8 Flash $2.74, MiniMax M2.5 $0.62.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 3.8 Flash 70.5 from 2 benchmarks, MiniMax M2.5 59.4 from 2 benchmarks.
Widest category: Agentic work, 31.8 points apart on average over 1 shared benchmark.
Widest single gap: ARC-AGI-2: Gemini 3.8 Flash 89.2% against MiniMax M2.5 4.9%, 84.3 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $4.125 against MiniMax M2.5 $0.95 per million output tokens, 4.3x apart.
Context window: Gemini 3.8 Flash takes 1.05M tokens, MiniMax M2.5 205K.

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	Gemini 3.8 Flash	Bars	MiniMax M2.5	Ties
Coding	9		0
Intelligence	2		0
Agentic work	1		0
Reasoning	8		0
Math	3		0
Knowledge	7		0
Web design	7		0
General	18		0
All shared boards	55		0

CodingLike-for-likeFour of these boards feed the Vibe Coding Index90

Coding benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
SWE-bench Verified	Not measured	75.8%	Only MiniMax M2.5 measured
SWE-bench Multilingual	Not measured	68.3%	Only MiniMax M2.5 measured
LiveBench coding	82.2%	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev	1585	1386	Gemini 3.8 Flash
AA Coding Index	76.3	Not measured	Only Gemini 3.8 Flash measured
LiveCodeBench (Vals AI)	89.5%	79.2%	Gemini 3.8 Flash
SWE-bench Verified (Vals AI)	80.0%	74.2%	Gemini 3.8 Flash
Terminal-Bench 4 (Vals AI)	19.7%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench (Vals AI)	78.7%	14.8%	Gemini 3.8 Flash
Code migration (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
ProgramBench (Vals AI)	1.0%	Not measured	Only Gemini 3.8 Flash measured
IOI (Vals AI)	56.9%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench 2.1 (Vals AI)	81.3%	Not measured	Only Gemini 3.8 Flash measured
SWE-bench Multimodal (Vals AI)	40.8%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
SkillsBench (Vals AI)	58.0%	Not measured	Only Gemini 3.8 Flash measured
CyberBench (Vals AI)	43.8%	Not measured	Only Gemini 3.8 Flash measured
SciCode	56.6%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	34.8%	Only MiniMax M2.5 measured
Terminal-Bench	Not measured	42.7%	Only MiniMax M2.5 measured
FrontierCode	41.2%	Not measured	Only Gemini 3.8 Flash measured
FrontierSWE	19.6%	Not measured	Only Gemini 3.8 Flash measured
WeirdML	84.8%	Not measured	Only Gemini 3.8 Flash measured
ALE-Bench	1269.7	618.2	Gemini 3.8 Flash
LMArena Text: coding	1508	1380	Gemini 3.8 Flash
LMArena Text: software and IT	1507	1383	Gemini 3.8 Flash
LMArena WebDev: React	1577	1374	Gemini 3.8 Flash
LMArena WebDev: HTML	1616	1414	Gemini 3.8 Flash
LMArena WebDev: from an image	1593	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 9 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
AA Intelligence Index	40.9	22.8	Gemini 3.8 Flash
Epoch Capabilities Index	157.4	146.6	Gemini 3.8 Flash

Agentic workLike-for-likePublic boards, shown as published, kept out of the index10

Agentic work benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
AA Agentic Index	40.2	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building web apps	1238	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building full-stack apps	1244	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building mobile apps	1236	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building Android apps	1078	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building Godot games	1273	Not measured	Only Gemini 3.8 Flash measured
Design Arena: PowerPoint slides	1178	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1052	Not measured	Only Gemini 3.8 Flash measured
LiveBench research	79.1%	Not measured	Only Gemini 3.8 Flash measured
LiveBench browser	64.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench long agentic	30.1%	Not measured	Only Gemini 3.8 Flash measured
SREBench (Vals AI)	11.1%	Not measured	Only Gemini 3.8 Flash measured
Finance Agent (Vals AI)	61.4%	Not measured	Only Gemini 3.8 Flash measured
Tax Agent Bench (Vals AI)	32.1%	Not measured	Only Gemini 3.8 Flash measured
Legal Research Bench (Vals AI)	38.9%	Not measured	Only Gemini 3.8 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)	12.1%	Not measured	Only Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)	72.2%	Not measured	Only Gemini 3.8 Flash measured
BioMysteryBench (Vals AI)	62.2%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench-Science (Vals AI)	8.6%	Not measured	Only Gemini 3.8 Flash measured
Vals Science Index	35.8%	Not measured	Only Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
CUA-bench (Vals AI)	4.2%	Not measured	Only Gemini 3.8 Flash measured
τ²-Bench Telecom	Not measured	95.3%	Only MiniMax M2.5 measured
APEX-Agents	64.3%	Not measured	Only Gemini 3.8 Flash measured
Remote Labor Index	5.8%	Not measured	Only Gemini 3.8 Flash measured
Vending-Bench 2	$5,094	-$23	Gemini 3.8 Flash
Neither model has a result on the other 13 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index80

Reasoning benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
GPQA Diamond	94.4%	82.1%	Gemini 3.8 Flash
LiveBench reasoning	89.3%	Not measured	Only Gemini 3.8 Flash measured
MysteryMechanism (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
MMMU Pro (Vals AI)	89.1%	Not measured	Only Gemini 3.8 Flash measured
GPQA Diamond (Artificial Analysis run)	95.3%	84.8%	Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)	47.8%	20.5%	Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)	95.4%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI	98.5%	63.7%	Gemini 3.8 Flash
ARC-AGI-2	89.2%	4.9%	Gemini 3.8 Flash
Chess puzzles	58.0%	Not measured	Only Gemini 3.8 Flash measured
Mystery game puzzles	47.0%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: hard prompts	1509	1372	Gemini 3.8 Flash
LMArena Text: expert	1526	1378	Gemini 3.8 Flash
LMArena Text: hard prompts in English	1504	1384	Gemini 3.8 Flash
LMArena Vision: diagrams	1345	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: homework	1351	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 5 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index30

Math benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
AIME	Not measured	88.8%	Only MiniMax M2.5 measured
OTIS Mock AIME	98.9%	Not measured	Only Gemini 3.8 Flash measured
FrontierMath, tiers 1 to 3	68.4%	Not measured	Only Gemini 3.8 Flash measured
FrontierMath, tier 4	22.0%	Not measured	Only Gemini 3.8 Flash measured
ProofBench	48.0%	4.0%	Gemini 3.8 Flash
LMArena Text: math	1532	1378	Gemini 3.8 Flash
LMArena Text: mathematical work	1519	1378	Gemini 3.8 Flash
Neither model has a result on the other 6 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70

Knowledge benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
MMLU Pro	90.2%	80.1%	Gemini 3.8 Flash
LegalBench (Vals AI)	87.0%	80.0%	Gemini 3.8 Flash
CaseLaw (Vals AI)	Not measured	53.5%	Only MiniMax M2.5 measured
CorpFin (Vals AI)	Not measured	59.6%	Only MiniMax M2.5 measured
TaxEval (Vals AI)	74.5%	68.2%	Gemini 3.8 Flash
MortgageTax (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
MedQA (Vals AI)	Not measured	92.5%	Only MiniMax M2.5 measured
MedCode (Vals AI)	48.1%	Not measured	Only Gemini 3.8 Flash measured
SimpleQA Verified	69.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: science	1523	1369	Gemini 3.8 Flash
LMArena Text: medicine and healthcare	1508	1357	Gemini 3.8 Flash
LMArena Text: legal and government	1497	1366	Gemini 3.8 Flash
LMArena Text: business and finance	1479	1356	Gemini 3.8 Flash
Neither model has a result on the other 4 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index70

Web design benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
Design Arena: websites	1301	1222	Gemini 3.8 Flash
Design Arena: UI components	1318	1172	Gemini 3.8 Flash
Design Arena: game dev	1305	1176	Gemini 3.8 Flash
Design Arena: data viz	1269	1171	Gemini 3.8 Flash
Design Arena: 3D	1295	1170	Gemini 3.8 Flash
Design Arena: all code categories	1304	1207	Gemini 3.8 Flash
Design Arena: SVG	1295	1147	Gemini 3.8 Flash
Design Arena: ASCII art	1264	Not measured	Only Gemini 3.8 Flash measured
LiveBench design	72.7%	Not measured	Only Gemini 3.8 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index180

General benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	Leader
Vals Index	56.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench data analysis	54.0%	Not measured	Only Gemini 3.8 Flash measured
Public Benefits Bench (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
SAGE (Vals AI)	35.1%	Not measured	Only Gemini 3.8 Flash measured
MedScribe (Vals AI)	84.5%	Not measured	Only Gemini 3.8 Flash measured
IFBench	Not measured	71.6%	Only MiniMax M2.5 measured
Long context reasoning (AA-LCR)	84.0%	73.3%	Gemini 3.8 Flash
DTBench	95.7%	Not measured	Only Gemini 3.8 Flash measured
LMCA	52.9%	Not measured	Only Gemini 3.8 Flash measured
CL-bench	Not measured	11.4%	Only MiniMax M2.5 measured
Surface Evolver Bench	76.9%	Not measured	Only Gemini 3.8 Flash measured
Furniture assembly	31.7%	Not measured	Only Gemini 3.8 Flash measured
CL-bench Life	Not measured	6.3%	Only MiniMax M2.5 measured
LMArena Text	1499	1359	Gemini 3.8 Flash
LMArena Text: instruction following	1492	1353	Gemini 3.8 Flash
LMArena Text: creative writing	1488	1331	Gemini 3.8 Flash
LMArena Vision	1315	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: English	1498	1380	Gemini 3.8 Flash
LMArena Text: non-English	1491	1338	Gemini 3.8 Flash
LMArena Text: Chinese	1553	1393	Gemini 3.8 Flash
LMArena Text: German	1501	1361	Gemini 3.8 Flash
LMArena Text: Japanese	1507	1171	Gemini 3.8 Flash
LMArena Text: Korean	1464	1233	Gemini 3.8 Flash
LMArena Text: French	1496	1363	Gemini 3.8 Flash
LMArena Text: Spanish	1487	1353	Gemini 3.8 Flash
LMArena Text: Russian	1514	1359	Gemini 3.8 Flash
LMArena Text: Polish	1497	1334	Gemini 3.8 Flash
LMArena Text: multi-turn	1503	1364	Gemini 3.8 Flash
LMArena Text: longer queries	1507	1366	Gemini 3.8 Flash
LMArena Text: writing and language	1494	1345	Gemini 3.8 Flash
LMArena Text: entertainment and media	1480	1329	Gemini 3.8 Flash
LMArena Vision: English	1318	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: Chinese	1416	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: reading text	1333	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: humor	1321	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: creative writing	1299	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 10 boards here

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

Image generation benchmarks for Gemini 3.8 Flash and MiniMax M2.5
Benchmark	Gemini 3.8 Flash	MiniMax M2.5	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

Gemini 3.8 Flash$0.0029Fits in one request

MiniMax M2.5$0.0007Fits in one request

MiniMax M2.5 costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.054Fits in one request

MiniMax M2.5$0.016Fits in one request

MiniMax M2.5 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.206Fits in one request

MiniMax M2.5$0.064Exceeds the context window

MiniMax M2.5 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 Gemini 3.8 Flash and MiniMax M2.5
Specification	Google Gemini 3.8 Flash	MiniMax M2.5
Maker	Google	MiniMax
Weights	No public weights listed	Open weights
Released	September 2, 2026	February 12, 2026
Context window	1.05M	205K
Input $/Mtok	$0.825	$0.27
Output $/Mtok	$4.125	$0.95
Coding index	70.5	59.4
Independent measurements behind it	2	2
Cost per solved task	$2.74	$0.62
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than MiniMax M2.5 for coding?

Pick Gemini 3.8 Flash for coding: it scores 70.5 on the Vibe Coding Index against 59.4 for MiniMax M2.5. Pick MiniMax M2.5 when output tokens cost 4.3x less, or when a solved task costs $0.62 against $2.74.

Which is cheaper, Gemini 3.8 Flash or MiniMax M2.5?

Gemini 3.8 Flash costs $0.825 per million input tokens and $4.125 per million output tokens; MiniMax M2.5 costs $0.27 and $0.95. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and MiniMax M2.5 $0.62.

Which has the bigger context window, Gemini 3.8 Flash or MiniMax M2.5?

Gemini 3.8 Flash, with 1.05M tokens against 205K.

How many benchmarks is the Gemini 3.8 Flash vs MiniMax M2.5 comparison based on?

55 benchmarks have a result for both models as of October 21, 2026. Gemini 3.8 Flash's coding index rests on 2 independent benchmarks and MiniMax M2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/gemini-3-8-flash-vs-minimax-minimax-m2-5" title="Gemini 3.8 Flash vs MiniMax M2.5, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
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Decision reading

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

General

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