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DeepSeek V4 Flash 0423 vs Llama 3.2 1B Instruct

Updated October 21, 2026. 24 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V4 Flash 0423 Replace Llama 3.2 1B Instruct
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
24.4
Output $/M
$0.28
24
Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
4.8
Output $/M
$0.201
0
vs boards won of 24 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

DeepSeek V4 Flash 0423 has the edge where the context window is larger, 1.05M against 60K tokens.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BLlama 3.2 1B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
24
DeepSeek V4 Flash 0423 only
24
Llama 3.2 1B Instruct only
13
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
DeepSeek V4 Flash 0423 not benchmarked, Llama 3.2 1B Instruct not benchmarked.
Widest category
Knowledge, 67.7 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: Chinese: DeepSeek V4 Flash 0423 1463 against Llama 3.2 1B Instruct 959, 77.2 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Llama 3.2 1B Instruct $0.201 per million output tokens, 1.4x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Llama 3.2 1B Instruct 60K.

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
CategoryDeepSeek V4 Flash 0423BarsLlama 3.2 1B InstructTies
Coding20
Intelligence10
Reasoning30
Math20
Knowledge40
General120
All shared boards240
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Artificial Analysis run)Not measured1.9%Only Llama 3.2 1B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured0.0%Only Llama 3.2 1B Instruct measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571070DeepSeek V4 Flash 0423
LMArena Text: software and IT14531056DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
AA Intelligence Index24.44.8DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured0.0%Only Llama 3.2 1B Instruct measured
BALROGNot measured6.6%Only Llama 3.2 1B Instruct measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
GPQA Diamond (Artificial Analysis run)Not measured19.6%Only Llama 3.2 1B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured5.5%Only Llama 3.2 1B Instruct measured
GPQA Diamond (Epoch AI run)Not measured23.9%Only Llama 3.2 1B Instruct measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441044DeepSeek V4 Flash 0423
LMArena Text: expert14411007DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491087DeepSeek V4 Flash 0423
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
AA Math IndexNot measured0.0Only Llama 3.2 1B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured0.0%Only Llama 3.2 1B Instruct measured
OTIS Mock AIMENot measured0.6%Only Llama 3.2 1B Instruct measured
LMArena Text: math14261086DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321098DeepSeek V4 Flash 0423
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
MMLU Pro (Artificial Analysis run)Not measured20.0%Only Llama 3.2 1B Instruct measured
LMArena Text: science14461055DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481009DeepSeek V4 Flash 0423
LMArena Text: legal and government14391071DeepSeek V4 Flash 0423
LMArena Text: business and finance14251000DeepSeek V4 Flash 0423
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
Design Arena: websites1208Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: UI components1165Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: game dev1197Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: data viz1127Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: 3D1189Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: all code categories1205Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: SVG1155Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
IFBenchNot measured22.8%Only Llama 3.2 1B Instruct measured
Long context reasoning (AA-LCR)Not measured6.7%Only Llama 3.2 1B Instruct measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321055DeepSeek V4 Flash 0423
LMArena Text: instruction following14211031DeepSeek V4 Flash 0423
LMArena Text: creative writing14031033DeepSeek V4 Flash 0423
LMArena Text: English14411117DeepSeek V4 Flash 0423
LMArena Text: non-English1419973DeepSeek V4 Flash 0423
LMArena Text: Chinese1463959DeepSeek V4 Flash 0423
LMArena Text: German14191014DeepSeek V4 Flash 0423
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean1383Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: French1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Spanish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Russian1427941DeepSeek V4 Flash 0423
LMArena Text: Polish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: multi-turn14491030DeepSeek V4 Flash 0423
LMArena Text: longer queries14341050DeepSeek V4 Flash 0423
LMArena Text: writing and language14101030DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001025DeepSeek V4 Flash 0423
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
BenchmarkDeepSeek V4 Flash 0423Llama 3.2 1B InstructLeader
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

DeepSeek V4 Flash 0423$0.0003Fits in one request
Llama 3.2 1B Instruct$0.0001Fits in one request

Llama 3.2 1B Instruct costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Llama 3.2 1B Instruct$0.0020Fits in one request

Llama 3.2 1B Instruct costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Llama 3.2 1B Instruct$0.0074Exceeds the context window

Llama 3.2 1B Instruct 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 DeepSeek V4 Flash 0423 and Llama 3.2 1B Instruct
SpecificationDeepSeek V4 Flash 0423Meta Llama 3.2 1B Instruct
MakerDeepSeekMeta Llama
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026September 25, 2024
Context window1.05M60K
Input $/Mtok$0.14$0.027
Output $/Mtok$0.28$0.201
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Llama 3.2 1B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. DeepSeek V4 Flash 0423 has the edge where the context window is larger, 1.05M against 60K tokens.

Which is cheaper, DeepSeek V4 Flash 0423 or Llama 3.2 1B Instruct?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; Llama 3.2 1B Instruct costs $0.027 and $0.201. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Llama 3.2 1B Instruct?

DeepSeek V4 Flash 0423, with 1.05M tokens against 60K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Llama 3.2 1B Instruct comparison based on?

24 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Llama 3.2 1B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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