Gemini 3.8 Flash vs Kimi K3.1 Pro

Kimi K3.1 Pro leads Gemini 3.8 Flash on coding, 82.2 to 61.6 on the Vibe Coding Index, and Gemini 3.8 Flash costs 2.7x less per output token ($3.75 vs $10.00 per million). Updated October 29, 2026; 35 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace Kimi K3.1 Pro

Gemini 3.8 FlashGoogle

Coding: 61.6
Overall: 65.5
Output $/M: $3.75

Kimi K3.1 ProMoonshot AI

Coding: 82.2
Overall: 74.4
Output $/M: $10.00

vs boards won of 35 shared

Gemini 3.8 Flash or Kimi K3.1 Pro: which to pick

Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash, though on 4 benchmarks against 6.

Pick Gemini 3.8 Flash for output tokens 2.7x cheaper ($3.75 vs $10.00 per million) and work measured by LiveBench coding or LiveBench research, where it leads.

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task Model BKimi K3.1 ProMoonshot AI82.2/1004 independent benchmarksNo cost per solved task

35101

Shared results: 35
Gemini 3.8 Flash only: 101
Kimi K3.1 Pro only: 0
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
Kimi K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 61.6.
6 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 46.0 against 30.5.
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
No call
Only Gemini 3.8 Flash has a GPQA Diamond result, 94.4%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.8 Flash has a MMLU Pro result, 90.2%.
Directional only
Web design
Design Arena: websites
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 1325 against 1299.
Same board, both measured
General
Vals Index
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 62.5% against 56.0%.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.8 Flash
Gemini 3.8 Flash $0.0026, Kimi K3.1 Pro $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.8 Flash has the number, $2.74.
Directional only

At a glance

Coding index: Gemini 3.8 Flash 61.6 from 6 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
Widest category: Math, 34.5 points apart on average over 2 shared benchmarks.
Widest single gap: Terminal-Bench 4 (Vals AI): Gemini 3.8 Flash 19.7% against Kimi K3.1 Pro 63.6%, 58.6 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $3.75 against Kimi K3.1 Pro $10.00 per million output tokens, 2.7x apart.
Context window: Both take 1.05M tokens.

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	Kimi K3.1 Pro
Coding	1	8
Intelligence	0	1
Agentic work	4	5
Reasoning	1	2
Math	0	2
Web design	0	8
General	0	3
All shared boards	6	29

CodingLike-for-likeSix of these boards feed the Vibe Coding Index18

Coding benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
LiveBench coding	82.2%	81.8%	Gemini 3.8 Flash
LMArena WebDev	1583	1695	Kimi K3.1 Pro
AA Coding Index	76.3	Not measured	Only Gemini 3.8 Flash measured
LiveCodeBench (Vals AI)	89.5%	Not measured	Only Gemini 3.8 Flash measured
SWE-bench Verified (Vals AI)	80.0%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench 4 (Vals AI)	19.7%	63.6%	Kimi K3.1 Pro
Vibe Code Bench (Vals AI)	78.7%	84.9%	Kimi K3.1 Pro
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%	81.9%	Kimi K3.1 Pro
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%	60.8%	Kimi K3.1 Pro
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	1932.8	Kimi K3.1 Pro
LMArena Text: coding	1509	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: software and IT	1507	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev: React	1577	1701	Kimi K3.1 Pro
LMArena WebDev: HTML	1612	1706	Kimi K3.1 Pro
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
SWE-Bench Pro V2	94.9%	Not measured	Only Gemini 3.8 Flash measured
SWE Atlas: Codebase QnA	47.0%	Not measured	Only Gemini 3.8 Flash measured
SWE Atlas: Refactoring	44.8%	Not measured	Only Gemini 3.8 Flash measured
SWE Atlas: Test Writing	53.7%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 13 boards here

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

Intelligence benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
AA Intelligence Index	30.5	46.0	Kimi K3.1 Pro
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 index45

Agentic work benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
AA Agentic Index	40.2	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building web apps	1240	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	1235	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building Android apps	1080	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	1138	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1058	Not measured	Only Gemini 3.8 Flash measured
LiveBench research	79.1%	77.9%	Gemini 3.8 Flash
LiveBench browser	45.1%	75.9%	Kimi K3.1 Pro
LiveBench long agentic	16.5%	39.1%	Kimi K3.1 Pro
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%	24.9%	Gemini 3.8 Flash
Legal Research Bench (Vals AI)	38.9%	37.5%	Gemini 3.8 Flash
Harvey's Legal Agent Benchmark (Vals AI)	12.1%	11.7%	Gemini 3.8 Flash
Excel Modeling Benchmark (Vals AI)	72.2%	Not measured	Only Gemini 3.8 Flash measured
BioMysteryBench (Vals AI)	62.2%	75.6%	Kimi K3.1 Pro
Terminal-Bench-Science (Vals AI)	8.6%	31.4%	Kimi K3.1 Pro
Vals Science Index	35.8%	44.4%	Kimi K3.1 Pro
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
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 17 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index12

Reasoning benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
GPQA Diamond	94.4%	Not measured	Only Gemini 3.8 Flash measured
LiveBench reasoning	89.3%	91.1%	Kimi K3.1 Pro
MysteryMechanism (Vals AI)	36.5%	26.1%	Gemini 3.8 Flash
MMMU Pro (Vals AI)	89.1%	Not measured	Only Gemini 3.8 Flash measured
GPQA Diamond (Artificial Analysis run)	95.3%	Not measured	Only Gemini 3.8 Flash measured
Humanity's Last Exam (Artificial Analysis run)	47.8%	52.5%	Kimi K3.1 Pro
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	1508	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: expert	1526	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: hard prompts in English	1504	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: diagrams	1345	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: homework	1351	Not measured	Only Gemini 3.8 Flash measured
Humanity's Last Exam (Scale run)	34.3%	Not measured	Only Gemini 3.8 Flash 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 Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	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%	91.0%	Kimi K3.1 Pro
LMArena Text: math	1530	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: mathematical work	1519	Not measured	Only Gemini 3.8 Flash measured
MathArena	33.6%	59.6%	Kimi K3.1 Pro
Neither model has a result on the other 7 boards here

KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared

Knowledge benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
MMLU Pro	90.2%	Not measured	Only Gemini 3.8 Flash measured
LegalBench (Vals AI)	87.0%	Not measured	Only Gemini 3.8 Flash measured
TaxEval (Vals AI)	74.5%	Not measured	Only Gemini 3.8 Flash measured
MortgageTax (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash 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	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: medicine and healthcare	1506	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: legal and government	1500	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: business and finance	1480	Not measured	Only Gemini 3.8 Flash measured
FACTS Benchmark Suite	68.5%	Not measured	Only Gemini 3.8 Flash measured
PRBench Finance	49.5%	Not measured	Only Gemini 3.8 Flash measured
PRBench Legal	48.9%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 7 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index08

Web design benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
Design Arena: websites	1299	1325	Kimi K3.1 Pro
Design Arena: UI components	1314	1400	Kimi K3.1 Pro
Design Arena: game dev	1304	1410	Kimi K3.1 Pro
Design Arena: data viz	1274	1300	Kimi K3.1 Pro
Design Arena: 3D	1292	1451	Kimi K3.1 Pro
Design Arena: all code categories	1302	1354	Kimi K3.1 Pro
Design Arena: SVG	1292	1328	Kimi K3.1 Pro
Design Arena: ASCII art	1274	Not measured	Only Gemini 3.8 Flash measured
LiveBench design	72.7%	77.8%	Kimi K3.1 Pro

GeneralLike-for-likePublic boards, shown as published, kept out of the index03

General benchmarks for Gemini 3.8 Flash and Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	Leader
Vals Index	56.0%	62.5%	Kimi K3.1 Pro
LiveBench data analysis	54.0%	79.1%	Kimi K3.1 Pro
Public Benefits Bench (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
SAGE (Vals AI)	88.2%	Not measured	Only Gemini 3.8 Flash measured
MedScribe (Vals AI)	84.5%	Not measured	Only Gemini 3.8 Flash measured
Long context reasoning (AA-LCR)	84.0%	86.3%	Kimi K3.1 Pro
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	1498	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: instruction following	1493	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: creative writing	1491	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision	1315	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: English	1498	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: non-English	1492	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Chinese	1550	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: German	1507	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Japanese	1508	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Korean	1477	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: French	1494	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Spanish	1487	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Russian	1516	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: Polish	1499	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: multi-turn	1504	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: longer queries	1509	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: writing and language	1495	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: entertainment and media	1481	Not measured	Only Gemini 3.8 Flash measured
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 15 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 Kimi K3.1 Pro
Benchmark	Gemini 3.8 Flash	Kimi K3.1 Pro	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

Kimi K3.1 Pro$0.0070Fits in one request

Gemini 3.8 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request

Kimi K3.1 Pro$0.130Fits in one request

Gemini 3.8 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request

Kimi K3.1 Pro$0.500Fits in one request

Gemini 3.8 Flash 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 Kimi K3.1 Pro
Specification	Google Gemini 3.8 Flash	MoonshotAI Kimi K3.1 Pro
Maker	Google	Moonshot AI
Weights	No public weights listed	No public weights listed
Released	September 2, 2026	October 23, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.75	$2.00
Output $/Mtok	$3.75	$10.00
Coding index	61.6	82.2
Independent measurements behind it	6	4
Cost per solved task	$2.74	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than Kimi K3.1 Pro for coding?

Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash, though on 4 benchmarks against 6. Pick Gemini 3.8 Flash for output tokens 2.7x cheaper ($3.75 vs $10.00 per million) and work measured by LiveBench coding or LiveBench research, where it leads.

Which is cheaper, Gemini 3.8 Flash or Kimi K3.1 Pro?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for Gemini 3.8 Flash only.

Which has the bigger context window, Gemini 3.8 Flash or Kimi K3.1 Pro?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.8 Flash vs Kimi K3.1 Pro comparison based on?

35 benchmarks have a result for both models as of October 29, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and Kimi K3.1 Pro's on 4. 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/gemini-3-8-flash-vs-kimi-k3-1-pro" title="Gemini 3.8 Flash vs Kimi K3.1 Pro, 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-kimi-k3-1-pro">LLMBenchmark.ai, Gemini 3.8 Flash vs Kimi K3.1 Pro</a></p>

Gemini 3.8 Flash or Kimi K3.1 Pro: 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