Noometry

Model comparison

Deepseek Coder v2 vs Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 35.9 on the Noometry Index.

Last verified . 17 shared benchmarks.

Deepseek Coder v2 DeepSeek

35.9

Rank #220 Confirmed

Gemini 2.5 Flash-Lite Google

37.0

Rank #211 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Deepseek Coder v2 scores higher in 2 categories and Gemini 2.5 Flash-Lite in 6 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Gemini 2.5 Flash-Lite leads 56.8 to 38.2.
  • Deepseek Coder v2 has downloadable open weights; the other is API-only.

Side by side

Deepseek Coder v2Gemini 2.5 Flash-Lite
ProviderDeepSeekGoogle
Noometry Index35.937.0
Released2024-06-172025-06-17
WeightsOpenProprietary
Context window—1.05M
Max output—66K
Input $ / M tokens—$0.10
Output $ / M tokens—$0.40
Results tracked2433

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Too close to call

Deepseek Coder v2: 38.1 (#183), Gemini 2.5 Flash-Lite: 38.5 (#173)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Coding12511373
WeirdML—35.2%
BigCodeBench Instruct48.2%—
BigCodeBench Complete59.7%—
ALE-Bench—325.9
HumanEval+82.3%—
MBPP+75.1%—

Agentic & Tool Use Not comparable

Deepseek Coder v2: —, Gemini 2.5 Flash-Lite: 28.0 (#96)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
Berkeley Function Calling Leaderboard—36.9%

Reasoning Deepseek Coder v2 leads

Deepseek Coder v2: 23.6 (#176), Gemini 2.5 Flash-Lite: 22.2 (#205)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Hard Prompts12071377
Kagi LLM Benchmark—40.5%
DTBench—62.8%
LMCA—18.1%
Epoch Capabilities Index—133.94
WinoGrande83.7%—

Math Gemini 2.5 Flash-Lite leads

Deepseek Coder v2: 34.9 (#190), Gemini 2.5 Flash-Lite: 38.0 (#144)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Math12411373
Omni-MATH—48%
GSM8K94.5%—

Knowledge Too close to call

Deepseek Coder v2: 32.3 (#212), Gemini 2.5 Flash-Lite: 32.5 (#210)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Expert11811373
MMLU-Pro—53.7%
Vectara Hallucination Rate—3.3%
GPQA (HELM)—30.9%
ARC (AI2) Challenge64.3%—

Multimodal Not comparable

Deepseek Coder v2: —, Gemini 2.5 Flash-Lite: 29.1 (#114)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Vision—1198
VPCT—30%

Multilingual Gemini 2.5 Flash-Lite leads

Deepseek Coder v2: 36.3 (#240), Gemini 2.5 Flash-Lite: 49.3 (#134)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Non-English11821369
LMArena Chinese12011404
LMArena French11851388
LMArena German11641389
LMArena Japanese11261359
LMArena Korean11041360
LMArena Russian11881373
LMArena Spanish11531396

Instruction Following Gemini 2.5 Flash-Lite leads

Deepseek Coder v2: 61.7 (#242), Gemini 2.5 Flash-Lite: 70.0 (#168)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Instruction Following11801367
IFEval—81%

Long Context Deepseek Coder v2 leads

Deepseek Coder v2: 37.0 (#224), Gemini 2.5 Flash-Lite: 33.3 (#262)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Longer Query12191373
Fiction.LiveBench—47.2%

Writing & Preference Gemini 2.5 Flash-Lite leads

Deepseek Coder v2: 38.2 (#253), Gemini 2.5 Flash-Lite: 56.8 (#135)

BenchmarkDeepseek Coder v2Gemini 2.5 Flash-Lite
LMArena Text11911379
LMArena Creative Writing11201367
LMArena Multi-Turn11771366
WildBench—81.8%

Frequently asked questions

Is Deepseek Coder v2 better than Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 35.9 on the Noometry Index.

Is Deepseek Coder v2 or Gemini 2.5 Flash-Lite better for coding?

They score almost the same on coding (38.1 vs 38.5); test both on your own repository before choosing.

How many benchmarks do Deepseek Coder v2 and Gemini 2.5 Flash-Lite share?

17 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Gemini 2.5 Flash-Lite has 33.

Related comparisons

Go deeper