Gemini 3.8 Flash vs MiMo-V2.5

Gemini 3.8 Flash leads MiMo-V2.5 on coding, 61.6 to 50.0 on the Vibe Coding Index, and MiMo-V2.5 costs 11.2x less per output token ($0.336 vs $3.75 per million). Updated October 22, 2026; 74 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace MiMo-V2.5

Gemini 3.8 FlashGoogle

Coding: 61.6
Overall: 69.0
Output $/M: $3.75

MiMo-V2.5Xiaomi

Coding: 50.0
Overall: 50.7
Output $/M: $0.336

vs boards won of 74 shared

Gemini 3.8 Flash or MiMo-V2.5: which to pick

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 50.0 for MiMo-V2.5.

Pick MiMo-V2.5 for output tokens 11.2x cheaper ($0.336 vs $3.75 per million) and a lower cost per solved task ($0.01 against $2.74).

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task Model BMiMo-V2.5Xiaomi50.0/1003 independent benchmarks$0.01 per solved task

74546

Shared results: 74
Gemini 3.8 Flash only: 54
MiMo-V2.5 only: 6
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
Gemini 3.8 Flash
Gemini 3.8 Flash scores 61.6 against 50.0.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 21.8.
Same board, both measured
Agentic work
AA Agentic Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.2 against 15.8.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 94.4% against 81.6%.
Same board, both measured
Knowledge
MMLU Pro
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 90.2% against 82.9%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1300 against 1265.
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
MiMo-V2.5
MiMo-V2.5 takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5
Gemini 3.8 Flash $0.0026, MiMo-V2.5 $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5
Gemini 3.8 Flash $2.74, MiMo-V2.5 $0.01.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 3.8 Flash 61.6 from 6 benchmarks, MiMo-V2.5 50.0 from 3 benchmarks.
Widest category: Agentic work, 24.1 points apart on average over 5 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): Gemini 3.8 Flash 78.7% against MiMo-V2.5 42.2%, 36.5 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $3.75 against MiMo-V2.5 $0.336 per million output tokens, 11.2x apart.
Context window: Gemini 3.8 Flash takes 1.05M tokens, MiMo-V2.5 1.05M.

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	MiMo-V2.5
Coding	13	0
Intelligence	1	0
Agentic work	5	0
Reasoning	9	0
Math	3	0
Knowledge	9	0
Web design	8	0
General	25	1
All shared boards	73	1

CodingLike-for-likeSix of these boards feed the Vibe Coding Index130

Coding benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
LiveBench coding	82.2%	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev	1585	1438	Gemini 3.8 Flash
AA Coding Index	76.3	56.8	Gemini 3.8 Flash
LiveCodeBench (Vals AI)	89.5%	81.5%	Gemini 3.8 Flash
SWE-bench Verified (Vals AI)	80.0%	71.0%	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%	42.2%	Gemini 3.8 Flash
Code migration (Vals AI)	36.5%	14.2%	Gemini 3.8 Flash
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%	60.7%	Gemini 3.8 Flash
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%	43.9%	Gemini 3.8 Flash
Terminal-Bench Hard (Artificial Analysis run)	Not measured	41.7%	Only MiMo-V2.5 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	514.0	Gemini 3.8 Flash
LMArena Text: coding	1508	1469	Gemini 3.8 Flash
LMArena Text: software and IT	1507	1463	Gemini 3.8 Flash
LMArena WebDev: React	1577	1425	Gemini 3.8 Flash
LMArena WebDev: HTML	1616	1429	Gemini 3.8 Flash
LMArena WebDev: from an image	1593	Not measured	Only Gemini 3.8 Flash measured
SciCode	12.3%	Not measured	Only Gemini 3.8 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 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
AA Intelligence Index	40.9	21.8	Gemini 3.8 Flash
Epoch Capabilities Index	157.4	Not measured	Only Gemini 3.8 Flash measured

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

Agentic work benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
AA Agentic Index	40.2	15.8	Gemini 3.8 Flash
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	1153	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1022	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%	36.7%	Gemini 3.8 Flash
Tax Agent Bench (Vals AI)	32.1%	7.8%	Gemini 3.8 Flash
Legal Research Bench (Vals AI)	38.9%	9.1%	Gemini 3.8 Flash
Harvey's Legal Agent Benchmark (Vals AI)	12.1%	Not measured	Only Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)	72.2%	55.1%	Gemini 3.8 Flash
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	90.6%	Only MiMo-V2.5 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	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 15 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index90

Reasoning benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
GPQA Diamond	94.4%	81.6%	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%	80.0%	Gemini 3.8 Flash
GPQA Diamond (Artificial Analysis run)	95.3%	84.9%	Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)	47.8%	27.2%	Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)	95.4%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI	98.5%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI-2	89.2%	Not measured	Only Gemini 3.8 Flash measured
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	1450	Gemini 3.8 Flash
LMArena Text: expert	1526	1459	Gemini 3.8 Flash
LMArena Text: hard prompts in English	1504	1461	Gemini 3.8 Flash
LMArena Vision: diagrams	1345	1269	Gemini 3.8 Flash
LMArena Vision: homework	1351	1262	Gemini 3.8 Flash
Neither model has a result on the other 6 boards here

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

Math benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
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%	16.0%	Gemini 3.8 Flash
LMArena Text: math	1532	1436	Gemini 3.8 Flash
LMArena Text: mathematical work	1519	1451	Gemini 3.8 Flash
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90

Knowledge benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
MMLU Pro	90.2%	82.9%	Gemini 3.8 Flash
LegalBench (Vals AI)	87.0%	78.9%	Gemini 3.8 Flash
CorpFin (Vals AI)	Not measured	59.9%	Only MiMo-V2.5 measured
TaxEval (Vals AI)	74.5%	71.8%	Gemini 3.8 Flash
MortgageTax (Vals AI)	65.3%	59.3%	Gemini 3.8 Flash
MedCode (Vals AI)	48.1%	31.9%	Gemini 3.8 Flash
SimpleQA Verified	69.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: science	1523	1440	Gemini 3.8 Flash
LMArena Text: medicine and healthcare	1508	1432	Gemini 3.8 Flash
LMArena Text: legal and government	1497	1425	Gemini 3.8 Flash
LMArena Text: business and finance	1479	1432	Gemini 3.8 Flash
FACTS Benchmark Suite	69.4%	Not measured	Only Gemini 3.8 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 index80

Web design benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	Leader
Design Arena: websites	1300	1265	Gemini 3.8 Flash
Design Arena: UI components	1316	1255	Gemini 3.8 Flash
Design Arena: game dev	1304	1249	Gemini 3.8 Flash
Design Arena: data viz	1270	1250	Gemini 3.8 Flash
Design Arena: 3D	1294	1215	Gemini 3.8 Flash
Design Arena: all code categories	1303	1260	Gemini 3.8 Flash
Design Arena: SVG	1296	1179	Gemini 3.8 Flash
Design Arena: ASCII art	1262	1140	Gemini 3.8 Flash
LiveBench design	72.7%	Not measured	Only Gemini 3.8 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index251

General benchmarks for Gemini 3.8 Flash and MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	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%	43.3%	MiMo-V2.5
MedScribe (Vals AI)	84.5%	72.2%	Gemini 3.8 Flash
Vals Multimodal Index	Not measured	52.8%	Only MiMo-V2.5 measured
IFBench	Not measured	67.1%	Only MiMo-V2.5 measured
Long context reasoning (AA-LCR)	84.0%	73.0%	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
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
LMArena Text	1499	1428	Gemini 3.8 Flash
LMArena Text: instruction following	1492	1435	Gemini 3.8 Flash
LMArena Text: creative writing	1488	1393	Gemini 3.8 Flash
LMArena Vision	1315	1247	Gemini 3.8 Flash
LMArena Text: English	1498	1447	Gemini 3.8 Flash
LMArena Text: non-English	1491	1405	Gemini 3.8 Flash
LMArena Text: Chinese	1553	1469	Gemini 3.8 Flash
LMArena Text: German	1501	1421	Gemini 3.8 Flash
LMArena Text: Japanese	1507	1306	Gemini 3.8 Flash
LMArena Text: Korean	1464	1361	Gemini 3.8 Flash
LMArena Text: French	1496	1448	Gemini 3.8 Flash
LMArena Text: Spanish	1487	1414	Gemini 3.8 Flash
LMArena Text: Russian	1514	1396	Gemini 3.8 Flash
LMArena Text: Polish	1497	1413	Gemini 3.8 Flash
LMArena Text: multi-turn	1503	1445	Gemini 3.8 Flash
LMArena Text: longer queries	1507	1445	Gemini 3.8 Flash
LMArena Text: writing and language	1494	1409	Gemini 3.8 Flash
LMArena Text: entertainment and media	1480	1399	Gemini 3.8 Flash
LMArena Vision: English	1318	1259	Gemini 3.8 Flash
LMArena Vision: Chinese	1416	1326	Gemini 3.8 Flash
LMArena Vision: reading text	1333	1256	Gemini 3.8 Flash
LMArena Vision: humor	1321	1226	Gemini 3.8 Flash
LMArena Vision: recognizing things	Not measured	1189	Only MiMo-V2.5 measured
LMArena Vision: creative writing	1299	1230	Gemini 3.8 Flash
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 MiMo-V2.5
Benchmark	Gemini 3.8 Flash	MiMo-V2.5	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$0.0026Fits in one request

MiMo-V2.5$0.0003Fits in one request

MiMo-V2.5 costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request

MiMo-V2.5$0.0094Fits in one request

MiMo-V2.5 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request

MiMo-V2.5$0.037Fits in one request

MiMo-V2.5 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 MiMo-V2.5
Specification	Google Gemini 3.8 Flash	Xiaomi MiMo-V2.5
Maker	Google	Xiaomi
Weights	No public weights listed	Open weights
Released	September 2, 2026	April 22, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.75	$0.168
Output $/Mtok	$3.75	$0.336
Coding index	61.6	50.0
Independent measurements behind it	6	3
Cost per solved task	$2.74	$0.01
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than MiMo-V2.5 for coding?

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 50.0 for MiMo-V2.5. Pick MiMo-V2.5 for output tokens 11.2x cheaper ($0.336 vs $3.75 per million) and a lower cost per solved task ($0.01 against $2.74).

Which is cheaper, Gemini 3.8 Flash or MiMo-V2.5?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and MiMo-V2.5 $0.01.

Which has the bigger context window, Gemini 3.8 Flash or MiMo-V2.5?

MiMo-V2.5, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 3.8 Flash vs MiMo-V2.5 comparison based on?

74 benchmarks have a result for both models as of October 22, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and MiMo-V2.5's on 3. 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-xiaomi-mimo-v2-5" title="Gemini 3.8 Flash vs MiMo-V2.5, 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/gemini-3-8-flash-vs-xiaomi-mimo-v2-5">LLMBenchmark.ai, Gemini 3.8 Flash vs MiMo-V2.5</a></p>

Gemini 3.8 Flash or MiMo-V2.5: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

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