Noometry

Model comparison

DeepSeek V4.1 Flash vs Llama 3.1-70B

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 29.6 on the Noometry Index.

Last verified . 23 shared benchmarks.

DeepSeek V4.1 Flash DeepSeek

52.8

Rank #38 Confirmed

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

Summary

  • They share 23 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 9 categories and Llama 3.1-70B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 13.5.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for DeepSeek V4.1 Flash and 3.6% for Llama 3.1-70B.
  • DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.40 / $0.40 for Llama 3.1-70B.
  • DeepSeek V4.1 Flash accepts more context: 1M tokens versus 128K.

Side by side

DeepSeek V4.1 FlashLlama 3.1-70B
ProviderDeepSeekMeta
Noometry Index52.829.6
Released2026-09-092024-07-23
WeightsOpenOpen
Context window1M128K
Max output393K4K
Input $ / M tokens$0.15$0.40
Output $ / M tokens$0.60$0.40
Results tracked3735

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Category by category

Coding DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 52.9 (#32), Llama 3.1-70B: 30.3 (#296)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Coding15061260
LMArena WebDev1619—
SciCode51.9%—
WeirdML—9%
BigCodeBench Instruct—46.1%
BigCodeBench Complete—54.8%
ALE-Bench1,092—

Agentic & Tool Use DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 31.2 (#69), Llama 3.1-70B: 25.1 (#112)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
APEX-Agents39.5%—
TheAgentCompany—6.9%
BALROG—27.9%
GDP.pdf19.8%—

Reasoning DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 50.2 (#36), Llama 3.1-70B: 21.6 (#220)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Hard Prompts14831241
DTBench89.9%60%
LMCA47%14.8%
Epoch Capabilities Index154.9125.92
NYT Connections (extended)89.6%—
CritPt14.3%—
Mystery Game Puzzles43%—
Surface Evolver Bench46.3%—

Math DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 66.7 (#25), Llama 3.1-70B: 13.5 (#304)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
OTIS Mock AIME 2024-202598.3%3.6%
LMArena Math14771252
FrontierMath (Tiers 1-3)67.4%—
FrontierMath Tier 426.8%—
ProofBench54%—
Omni-MATH—21%
MATH Level 5—36.7%

Knowledge DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 57.9 (#38), Llama 3.1-70B: 24.2 (#269)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
GPQA Diamond89.8%44.2%
LMArena Expert15061209
MMLU-Pro—65.3%
GPQA (HELM)—42.6%
MMLU—80.1%

Multimodal Not comparable

DeepSeek V4.1 Flash: 39.1 (#61), Llama 3.1-70B: —

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Vision1277—
Furniture Assembly34.2%—

Multilingual DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 55.0 (#35), Llama 3.1-70B: 38.8 (#225)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Non-English14481219
LMArena Chinese14971215
LMArena French14521261
LMArena German14841222
LMArena Japanese14121132
LMArena Korean14521140
LMArena Russian14711234
LMArena Spanish14591253

Instruction Following DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 77.3 (#26), Llama 3.1-70B: 65.3 (#223)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Instruction Following14741231
IFEval—82.1%

Long Context DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 45.2 (#47), Llama 3.1-70B: 37.6 (#214)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Longer Query14751241

Writing & Preference DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 65.4 (#48), Llama 3.1-70B: 35.4 (#267)

BenchmarkDeepSeek V4.1 FlashLlama 3.1-70B
LMArena Text14621261
LMArena Creative Writing14351232
EQ-Bench Creative Writing1540784
LMArena Multi-Turn14571256
WildBench—75.8%

Frequently asked questions

Is DeepSeek V4.1 Flash better than Llama 3.1-70B?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 29.6 on the Noometry Index.

Which is cheaper, DeepSeek V4.1 Flash or Llama 3.1-70B?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Llama 3.1-70B lists at $0.40 and $0.40.

Is DeepSeek V4.1 Flash or Llama 3.1-70B better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 128K.

How many benchmarks do DeepSeek V4.1 Flash and Llama 3.1-70B share?

23 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Llama 3.1-70B has 35.

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