Gemini 3.7 Flash vs MiniMax M2

Gemini 3.7 Flash leads MiniMax M2 on the Artificial Analysis Intelligence Index, 39.6 to 18.6, and MiniMax M2 costs 3.7x less per output token ($1.02 vs $3.75 per million). Updated October 22, 2026; 39 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace MiniMax M2

Gemini 3.7 FlashGoogle

Coding: 58.0
Overall: 65.7
Output $/M: $3.75

MiniMax M2MiniMax

Coding: No data
Overall: No data
Output $/M: $1.02

vs boards won of 39 shared

Gemini 3.7 Flash or MiniMax M2: which to pick

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding.

Pick MiniMax M2 for output tokens 3.7x cheaper ($1.02 vs $3.75 per million) and a lower cost per solved task ($0.702 against $1.78).

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved task Model BMiniMax M2MiniMaxNot benchmarked1 independent benchmark$0.702 per solved task

397511

Shared results: 39
Gemini 3.7 Flash only: 75
MiniMax M2 only: 11
Like-for-like categories: 7 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
No call
Only Gemini 3.7 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 39.6 against 18.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1303 against 1143.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2
Gemini 3.7 Flash $0.0026, MiniMax M2 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2
Gemini 3.7 Flash $1.78, MiniMax M2 $0.702.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 3.7 Flash 58.0 from 6 benchmarks, MiniMax M2 not benchmarked.
Widest category: Coding, 33.0 points apart on average over 4 shared benchmarks.
Widest single gap: LMArena WebDev: HTML: Gemini 3.7 Flash 1593 against MiniMax M2 1306, 47.8 points apart on a 0 to 100 scale.
Output price: Gemini 3.7 Flash $3.75 against MiniMax M2 $1.02 per million output tokens, 3.7x apart.
Context window: Gemini 3.7 Flash takes 1.05M tokens, MiniMax M2 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 3.7 Flash	Bars	MiniMax M2	Ties
Coding	4		0
Intelligence	1		0
Reasoning	5		0
Math	2		0
Knowledge	4		0
Web design	7		0
General	16		0
All shared boards	39		0

CodingLike-for-likeSix of these boards feed the Vibe Coding Index40

Coding benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
SWE-bench Verified	Not measured	61.0%	Only MiniMax M2 measured
LiveBench coding	80.5%	Not measured	Only Gemini 3.7 Flash measured
LMArena WebDev	1591	1297	Gemini 3.7 Flash
AA Coding Index	71.5	Not measured	Only Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)	88.7%	Not measured	Only Gemini 3.7 Flash measured
SWE-bench Verified (Vals AI)	80.8%	Not measured	Only Gemini 3.7 Flash measured
Terminal-Bench 4 (Vals AI)	12.1%	Not measured	Only Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)	70.4%	Not measured	Only Gemini 3.7 Flash measured
Code migration (Vals AI)	34.8%	Not measured	Only Gemini 3.7 Flash measured
ProgramBench (Vals AI)	0.0%	Not measured	Only Gemini 3.7 Flash measured
IOI (Vals AI)	67.8%	Not measured	Only Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)	77.5%	Not measured	Only Gemini 3.7 Flash measured
SkillsBench (Vals AI)	65.9%	Not measured	Only Gemini 3.7 Flash measured
CyberBench (Vals AI)	43.8%	Not measured	Only Gemini 3.7 Flash measured
LiveCodeBench (Artificial Analysis run)	Not measured	82.6%	Only MiniMax M2 measured
SciCode	59.8%	Not measured	Only Gemini 3.7 Flash measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	25.8%	Only MiniMax M2 measured
Terminal-Bench	Not measured	30.0%	Only MiniMax M2 measured
FrontierCode	43.6%	Not measured	Only Gemini 3.7 Flash measured
FrontierSWE	20.3%	Not measured	Only Gemini 3.7 Flash measured
ALE-Bench	904.3	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: coding	1499	1371	Gemini 3.7 Flash
LMArena Text: software and IT	1498	1373	Gemini 3.7 Flash
LMArena WebDev: React	1587	Not measured	Only Gemini 3.7 Flash measured
LMArena WebDev: HTML	1593	1306	Gemini 3.7 Flash
LMArena WebDev: from an image	1599	Not measured	Only Gemini 3.7 Flash measured
SciCode	13.8%	Not measured	Only Gemini 3.7 Flash measured
Neither model has a result on the other 12 boards here

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

Intelligence benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
AA Intelligence Index	39.6	18.6	Gemini 3.7 Flash
Epoch Capabilities Index	158.0	Not measured	Only Gemini 3.7 Flash measured

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared

Agentic work benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
Design Arena: agents building web apps	1223	Not measured	Only Gemini 3.7 Flash measured
Design Arena: agents building full-stack apps	1208	Not measured	Only Gemini 3.7 Flash measured
Design Arena: agents building mobile apps	1230	Not measured	Only Gemini 3.7 Flash measured
Design Arena: agents building Android apps	1243	Not measured	Only Gemini 3.7 Flash measured
Design Arena: agents building Godot games	1264	Not measured	Only Gemini 3.7 Flash measured
Design Arena: agents building games	1235	Not measured	Only Gemini 3.7 Flash measured
Design Arena: spreadsheets	1091	Not measured	Only Gemini 3.7 Flash measured
LiveBench research	76.5%	Not measured	Only Gemini 3.7 Flash measured
LiveBench browser	56.0%	Not measured	Only Gemini 3.7 Flash measured
LiveBench long agentic	28.3%	Not measured	Only Gemini 3.7 Flash measured
SREBench (Vals AI)	4.6%	Not measured	Only Gemini 3.7 Flash measured
Finance Agent (Vals AI)	59.0%	Not measured	Only Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)	22.8%	Not measured	Only Gemini 3.7 Flash measured
Legal Research Bench (Vals AI)	34.6%	Not measured	Only Gemini 3.7 Flash measured
Excel Modeling Benchmark (Vals AI)	71.3%	Not measured	Only Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)	7.1%	Not measured	Only Gemini 3.7 Flash measured
τ²-Bench Telecom	Not measured	86.8%	Only MiniMax M2 measured
APEX-Agents	67.8%	Not measured	Only Gemini 3.7 Flash measured
Remote Labor Index	5.0%	Not measured	Only Gemini 3.7 Flash measured
Vending-Bench 2	Not measured	$161	Only MiniMax M2 measured
Neither model has a result on the other 21 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index50

Reasoning benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
GPQA Diamond	93.9%	Not measured	Only Gemini 3.7 Flash measured
LiveBench reasoning	87.8%	Not measured	Only Gemini 3.7 Flash measured
MMMU Pro (Vals AI)	89.0%	Not measured	Only Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)	94.5%	77.7%	Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)	47.9%	13.7%	Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)	94.8%	Not measured	Only Gemini 3.7 Flash measured
ARC-AGI	95.5%	Not measured	Only Gemini 3.7 Flash measured
ARC-AGI-2	84.6%	Not measured	Only Gemini 3.7 Flash measured
Chess puzzles	66.0%	Not measured	Only Gemini 3.7 Flash measured
Mystery game puzzles	37.0%	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: hard prompts	1495	1357	Gemini 3.7 Flash
LMArena Text: expert	1512	1338	Gemini 3.7 Flash
LMArena Text: hard prompts in English	1487	1376	Gemini 3.7 Flash
LMArena Vision: diagrams	1329	Not measured	Only Gemini 3.7 Flash measured
LMArena Vision: homework	1320	Not measured	Only Gemini 3.7 Flash measured
Kagi LLM Benchmark	Not measured	57.8%	Only MiniMax M2 measured
Neither model has a result on the other 6 boards here

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

Math benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
AA Math Index	Not measured	78.3	Only MiniMax M2 measured
AIME 2025 (Artificial Analysis run)	Not measured	78.3%	Only MiniMax M2 measured
OTIS Mock AIME	97.2%	Not measured	Only Gemini 3.7 Flash measured
FrontierMath, tiers 1 to 3	71.6%	Not measured	Only Gemini 3.7 Flash measured
FrontierMath, tier 4	36.6%	Not measured	Only Gemini 3.7 Flash measured
ProofBench	58.0%	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: math	1511	1351	Gemini 3.7 Flash
LMArena Text: mathematical work	1502	1368	Gemini 3.7 Flash
Neither model has a result on the other 5 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40

Knowledge benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
MMLU Pro	90.1%	Not measured	Only Gemini 3.7 Flash measured
LegalBench (Vals AI)	87.3%	Not measured	Only Gemini 3.7 Flash measured
TaxEval (Vals AI)	74.7%	Not measured	Only Gemini 3.7 Flash measured
MortgageTax (Vals AI)	66.7%	Not measured	Only Gemini 3.7 Flash measured
MedCode (Vals AI)	53.4%	Not measured	Only Gemini 3.7 Flash measured
MMLU Pro (Artificial Analysis run)	Not measured	82.0%	Only MiniMax M2 measured
SimpleQA Verified	69.2%	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: science	1511	1348	Gemini 3.7 Flash
LMArena Text: medicine and healthcare	1494	1367	Gemini 3.7 Flash
LMArena Text: legal and government	1496	1349	Gemini 3.7 Flash
LMArena Text: business and finance	1479	1336	Gemini 3.7 Flash
FACTS Benchmark Suite	71.2%	Not measured	Only Gemini 3.7 Flash measured
Neither model has a result on the other 6 boards here

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

Web design benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
Design Arena: websites	1303	1143	Gemini 3.7 Flash
Design Arena: UI components	1295	1134	Gemini 3.7 Flash
Design Arena: game dev	1318	1118	Gemini 3.7 Flash
Design Arena: data viz	1315	1140	Gemini 3.7 Flash
Design Arena: 3D	1307	1098	Gemini 3.7 Flash
Design Arena: all code categories	1307	1135	Gemini 3.7 Flash
Design Arena: SVG	1283	1100	Gemini 3.7 Flash
Design Arena: ASCII art	1278	Not measured	Only Gemini 3.7 Flash measured
LiveBench design	73.2%	Not measured	Only Gemini 3.7 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index160

General benchmarks for Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	Leader
LiveBench data analysis	68.0%	Not measured	Only Gemini 3.7 Flash measured
SAGE (Vals AI)	49.2%	Not measured	Only Gemini 3.7 Flash measured
MedScribe (Vals AI)	83.9%	Not measured	Only Gemini 3.7 Flash measured
IFBench	Not measured	72.3%	Only MiniMax M2 measured
Long context reasoning (AA-LCR)	83.0%	64.3%	Gemini 3.7 Flash
DTBench	96.8%	Not measured	Only Gemini 3.7 Flash measured
LMCA	50.4%	Not measured	Only Gemini 3.7 Flash measured
Furniture assembly	26.7%	Not measured	Only Gemini 3.7 Flash measured
LMArena Text	1489	1340	Gemini 3.7 Flash
LMArena Text: instruction following	1484	1329	Gemini 3.7 Flash
LMArena Text: creative writing	1488	1286	Gemini 3.7 Flash
LMArena Vision	1314	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: English	1483	1364	Gemini 3.7 Flash
LMArena Text: non-English	1487	1313	Gemini 3.7 Flash
LMArena Text: Chinese	1552	1366	Gemini 3.7 Flash
LMArena Text: German	1506	1357	Gemini 3.7 Flash
LMArena Text: Japanese	1511	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: Korean	1481	Not measured	Only Gemini 3.7 Flash measured
LMArena Text: French	1500	1336	Gemini 3.7 Flash
LMArena Text: Spanish	1495	1326	Gemini 3.7 Flash
LMArena Text: Russian	1515	1330	Gemini 3.7 Flash
LMArena Text: Polish	1503	1312	Gemini 3.7 Flash
LMArena Text: multi-turn	1485	1361	Gemini 3.7 Flash
LMArena Text: longer queries	1492	1331	Gemini 3.7 Flash
LMArena Text: writing and language	1491	1295	Gemini 3.7 Flash
LMArena Text: entertainment and media	1477	1298	Gemini 3.7 Flash
LMArena Vision: English	1309	Not measured	Only Gemini 3.7 Flash measured
LMArena Vision: Chinese	1394	Not measured	Only Gemini 3.7 Flash measured
LMArena Vision: reading text	1322	Not measured	Only Gemini 3.7 Flash measured
LMArena Vision: humor	1299	Not measured	Only Gemini 3.7 Flash measured
LMArena Vision: creative writing	1312	Not measured	Only Gemini 3.7 Flash 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 Gemini 3.7 Flash and MiniMax M2
Benchmark	Gemini 3.7 Flash	MiniMax M2	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 3.7 Flash$0.0026Fits in one request

MiniMax M2$0.0008Fits in one request

MiniMax M2 costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request

MiniMax M2$0.016Fits in one request

MiniMax M2 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request

MiniMax M2$0.061Exceeds the context window

MiniMax M2 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 3.7 Flash and MiniMax M2
Specification	Google Gemini 3.7 Flash	MiniMax M2
Maker	Google	MiniMax
Weights	No public weights listed	Open weights
Released	August 13, 2026	October 23, 2025
Context window	1.05M	205K
Input $/Mtok	$0.75	$0.255
Output $/Mtok	$3.75	$1.02
Coding index	58.0	Not benchmarked
Independent measurements behind it	6	1
Cost per solved task	$1.78	$0.702
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.7 Flash better than MiniMax M2 for coding?

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding. Pick MiniMax M2 for output tokens 3.7x cheaper ($1.02 vs $3.75 per million) and a lower cost per solved task ($0.702 against $1.78).

Which is cheaper, Gemini 3.7 Flash or MiniMax M2?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and MiniMax M2 $0.702.

Which has the bigger context window, Gemini 3.7 Flash or MiniMax M2?

Gemini 3.7 Flash, with 1.05M tokens against 205K.

How many benchmarks is the Gemini 3.7 Flash vs MiniMax M2 comparison based on?

39 benchmarks have a result for both models as of October 22, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.

Gemini 3.7 Flash or MiniMax M2: which to pick

Which one for your work

Coding

Intelligence

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

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