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Gemini 2.5 Pro vs MiMo-V2.5-Pro

MiMo-V2.5-Pro leads Gemini 2.5 Pro on coding, 31.6 to 19.1 on the Vibe Coding Index, and MiMo-V2.5-Pro costs 10.9x less per output token ($0.9152 vs $10.00 per million). Updated October 22, 2026; 53 benchmarks have a result for both.

Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
14
MiMo-V2.5-ProXiaomi
Coding
31.6
Overall
39.3
Output $/M
$0.9152
39
vs boards won of 53 shared

Gemini 2.5 Pro or MiMo-V2.5-Pro: which to pick

Pick MiMo-V2.5-Pro for coding: it scores 31.6 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.

Pick Gemini 2.5 Pro for work measured by MedCode (Vals AI) or LMArena Text: medicine and healthcare, where it leads.

Shared results
53
Gemini 2.5 Pro only
37
MiMo-V2.5-Pro only
17
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.

At a glance

Coding index
Gemini 2.5 Pro 19.1 from 3 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
Widest category
Agentic work, 29.9 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against MiMo-V2.5-Pro 94.2%, 40.1 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against MiMo-V2.5-Pro $0.9152 per million output tokens, 10.9x apart.
Context window
Gemini 2.5 Pro takes 1.05M tokens, MiMo-V2.5-Pro 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
CategoryGemini 2.5 ProBarsMiMo-V2.5-ProTies
Coding09
Intelligence01
Agentic work02
Reasoning05
Math02
Knowledge33
Web design06
General1111
All shared boards1439
CodingLike-for-likeSix of these boards feed the Vibe Coding Index09
Coding benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev12261480MiMo-V2.5-Pro
AA Coding Index33.360.2MiMo-V2.5-Pro
LiveCodeBench (Vals AI)Not measured81.3%Only MiMo-V2.5-Pro measured
SWE-bench Verified (Vals AI)54.4%74.0%MiMo-V2.5-Pro
Terminal-Bench 4 (Vals AI)Not measured0.5%Only MiMo-V2.5-Pro measured
Vibe Code Bench (Vals AI)0.4%34.1%MiMo-V2.5-Pro
Code migration (Vals AI)Not measured21.6%Only MiMo-V2.5-Pro measured
Terminal-Bench 2.1 (Vals AI)Not measured57.3%Only MiMo-V2.5-Pro measured
LiveCodeBench (Artificial Analysis run)80.1%Not measuredOnly Gemini 2.5 Pro measured
SciCode46.3%50.6%MiMo-V2.5-Pro
Terminal-Bench Hard (Artificial Analysis run)26.5%43.2%MiMo-V2.5-Pro
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%Not measuredOnly Gemini 2.5 Pro measured
ALE-BenchNot measured899.8Only MiMo-V2.5-Pro measured
LMArena Text: coding14521501MiMo-V2.5-Pro
LMArena Text: software and IT14591495MiMo-V2.5-Pro
LMArena WebDev: ReactNot measured1469Only MiMo-V2.5-Pro measured
LMArena WebDev: HTML12351473MiMo-V2.5-Pro
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
AA Intelligence Index16.126.0MiMo-V2.5-Pro
Epoch Capabilities Index145.1Not measuredOnly Gemini 2.5 Pro measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
AA Agentic Index1.621.3MiMo-V2.5-Pro
Finance Agent (Vals AI)Not measured41.5%Only MiMo-V2.5-Pro measured
Tax Agent Bench (Vals AI)Not measured11.5%Only MiMo-V2.5-Pro measured
Legal Research Bench (Vals AI)Not measured15.9%Only MiMo-V2.5-Pro measured
Excel Modeling Benchmark (Vals AI)Not measured55.2%Only MiMo-V2.5-Pro measured
τ²-Bench Telecom54.1%94.2%MiMo-V2.5-Pro
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
DeepResearch Bench41.5%Not measuredOnly Gemini 2.5 Pro measured
Vending-Bench 2$574Not measuredOnly Gemini 2.5 Pro measured
BrowseComp-Plus29.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
GPQA DiamondNot measured82.6%Only MiMo-V2.5-Pro measured
GPQA Diamond (Artificial Analysis run)84.4%86.6%MiMo-V2.5-Pro
Humanity's Last Exam (Artificial Analysis run)22.5%35.7%MiMo-V2.5-Pro
GPQA Diamond (Epoch AI run)85.3%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI41.0%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI-24.9%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: hard prompts14551486MiMo-V2.5-Pro
LMArena Text: expert14521501MiMo-V2.5-Pro
LMArena Text: hard prompts in English14531494MiMo-V2.5-Pro
LMArena Vision: diagrams1274Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: homework1281Not measuredOnly Gemini 2.5 Pro measured
Kagi LLM Benchmark70.3%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
AA Math Index87.7Not measuredOnly Gemini 2.5 Pro measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly Gemini 2.5 Pro measured
OTIS Mock AIME84.7%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tiers 1 to 324.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
ProofBenchNot measured22.0%Only MiMo-V2.5-Pro measured
LMArena Text: math14501481MiMo-V2.5-Pro
LMArena Text: mathematical work14541491MiMo-V2.5-Pro
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
Knowledge benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
MMLU ProNot measured84.6%Only MiMo-V2.5-Pro measured
LegalBench (Vals AI)Not measured77.1%Only MiMo-V2.5-Pro measured
CaseLaw (Vals AI)63.9%Not measuredOnly Gemini 2.5 Pro measured
CorpFin (Vals AI)60.8%61.4%MiMo-V2.5-Pro
TaxEval (Vals AI)Not measured73.8%Only MiMo-V2.5-Pro measured
MortgageTax (Vals AI)68.9%Not measuredOnly Gemini 2.5 Pro measured
MedCode (Vals AI)50.6%32.5%Gemini 2.5 Pro
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: science14801482MiMo-V2.5-Pro
LMArena Text: medicine and healthcare14761473Gemini 2.5 Pro
LMArena Text: legal and government14801474Gemini 2.5 Pro
LMArena Text: business and finance14391466MiMo-V2.5-Pro
FACTS Benchmark Suite61.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
Design Arena: websites11671266MiMo-V2.5-Pro
Design Arena: UI components11371246MiMo-V2.5-Pro
Design Arena: game dev11111261MiMo-V2.5-Pro
Design Arena: data viz12221257MiMo-V2.5-Pro
Design Arena: 3D10801243MiMo-V2.5-Pro
Design Arena: all code categories11521265MiMo-V2.5-Pro
Design Arena: SVGNot measured1181Only MiMo-V2.5-Pro measured
Design Arena: ASCII artNot measured1156Only MiMo-V2.5-Pro measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index1111
General benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
SAGE (Vals AI)41.9%Not measuredOnly Gemini 2.5 Pro measured
MedScribe (Vals AI)73.5%83.7%MiMo-V2.5-Pro
IFBench48.7%79.9%MiMo-V2.5-Pro
Long context reasoning (AA-LCR)69.0%79.7%MiMo-V2.5-Pro
DTBench82.4%84.5%MiMo-V2.5-Pro
LMCA34.8%29.5%Gemini 2.5 Pro
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581464MiMo-V2.5-Pro
LMArena Text: instruction following14371475MiMo-V2.5-Pro
LMArena Text: creative writing14541438Gemini 2.5 Pro
LMArena Vision1263Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: English14581477MiMo-V2.5-Pro
LMArena Text: non-English14521448Gemini 2.5 Pro
LMArena Text: Chinese15071507Gemini 2.5 Pro
LMArena Text: German14871459Gemini 2.5 Pro
LMArena Text: Japanese14611410Gemini 2.5 Pro
LMArena Text: Korean14341435MiMo-V2.5-Pro
LMArena Text: French14731487MiMo-V2.5-Pro
LMArena Text: Spanish14741469Gemini 2.5 Pro
LMArena Text: Russian14611449Gemini 2.5 Pro
LMArena Text: Polish14791464Gemini 2.5 Pro
LMArena Text: multi-turn14531476MiMo-V2.5-Pro
LMArena Text: longer queries14491481MiMo-V2.5-Pro
LMArena Text: writing and language14541451Gemini 2.5 Pro
LMArena Text: entertainment and media14411438Gemini 2.5 Pro
LMArena Vision: English1261Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: Chinese1300Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: reading text1270Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: humor1262Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: captioning1304Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: recognizing things1283Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: creative writing1265Not measuredOnly Gemini 2.5 Pro measured
LMArena Document1421Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Pro and MiMo-V2.5-Pro
BenchmarkGemini 2.5 ProMiMo-V2.5-ProLeader
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 2.5 Pro$0.0063Fits in one request
MiMo-V2.5-Pro$0.0009Fits in one request

MiMo-V2.5-Pro costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro$0.092Fits in one request
MiMo-V2.5-Pro$0.026Fits in one request

MiMo-V2.5-Pro costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro$0.350Fits in one request
MiMo-V2.5-Pro$0.101Fits in one request

MiMo-V2.5-Pro 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 2.5 Pro and MiMo-V2.5-Pro
SpecificationGoogle Gemini 2.5 ProXiaomi MiMo-V2.5-Pro
MakerGoogleXiaomi
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025April 22, 2026
Context window1.05M1.05M
Input $/Mtok$1.25$0.4575
Output $/Mtok$10.00$0.9152
Coding index19.131.6
Independent measurements behind it34
Cost per solved task$0.64$0.03
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro better than MiMo-V2.5-Pro for coding?

Pick MiMo-V2.5-Pro for coding: it scores 31.6 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for work measured by MedCode (Vals AI) or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, Gemini 2.5 Pro or MiMo-V2.5-Pro?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and MiMo-V2.5-Pro $0.03.

Which has the bigger context window, Gemini 2.5 Pro or MiMo-V2.5-Pro?

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

How many benchmarks is the Gemini 2.5 Pro vs MiMo-V2.5-Pro comparison based on?

53 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-2-5-pro-vs-xiaomi-mimo-v2-5-pro">LLMBenchmark.ai, Gemini 2.5 Pro vs MiMo-V2.5-Pro</a></p>