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Llama 3.1 8B Instruct vs o1

Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Llama 3.1 8B Instruct Replace o1
Llama 3.1 8B InstructMeta Llama
Coding
No data
Overall
6.9
Output $/M
$0.08
0
o1OpenAI
Coding
No data
Overall
15.2
Output $/M
$60.00
44
vs boards won of 44 shared

Decision reading

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

Llama 3.1 8B Instruct has the edge where output tokens cost 750.0x less, and where what matters is AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.

Model ALlama 3.1 8B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bo1OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
44
Llama 3.1 8B Instruct only
6
o1 only
24
Like-for-like categories
7 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
Llama 3.1 8B Instruct not benchmarked, o1 not benchmarked.
Widest category
Math, 53.3 points apart on average over 4 shared benchmarks.
Widest single gap
MATH level 5: Llama 3.1 8B Instruct 22.9% against o1 94.7%, 71.8 points apart on a 0 to 100 scale.
Output price
Llama 3.1 8B Instruct $0.08 against o1 $60.00 per million output tokens, 750.0x apart.
Context window
Llama 3.1 8B Instruct takes 131K tokens, o1 200K.

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
CategoryLlama 3.1 8B InstructBarso1Ties
Coding06
Intelligence02
Agentic work01
Reasoning06
Math04
Knowledge05
General020
All shared boards044
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
Aider polyglotNot measured61.7%Only o1 measured
AA Coding Index5.439.7o1
LiveCodeBench (Vals AI)Not measured50.3%Only o1 measured
LiveCodeBench (Artificial Analysis run)11.6%67.9%o1
Terminal-Bench Hard (Artificial Analysis run)0.8%12.9%o1
WeirdML1.7%46.1%o1
LMArena Text: coding11951367o1
LMArena Text: software and IT11951366o1
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
AA Intelligence Index6.915.2o1
Epoch Capabilities Index116.5141.7o1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
τ²-Bench Telecom16.4%62.6%o1
METR time horizonsNot measured51.1%Only o1 measured
BALROG15.1%Not measuredOnly Llama 3.1 8B Instruct measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
GPQA DiamondNot measured73.2%Only o1 measured
MMMU Pro (Vals AI)Not measured77.4%Only o1 measured
GPQA Diamond (Artificial Analysis run)25.9%74.7%o1
Humanity's Last Exam (Artificial Analysis run)5.3%7.0%o1
GPQA Diamond (Epoch AI run)27.0%76.8%o1
ARC-AGINot measured30.7%Only o1 measured
SimpleBenchNot measured40.1%Only o1 measured
Chess puzzlesNot measured10.0%Only o1 measured
VPCTNot measured37.0%Only o1 measured
LMArena Text: hard prompts11751371o1
LMArena Text: expert11441361o1
LMArena Text: hard prompts in English11961372o1
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
AIMENot measured71.5%Only o1 measured
MATH 500 (Vals AI)Not measured90.4%Only o1 measured
MGSM (Vals AI)Not measured89.3%Only o1 measured
AA Math Index4.3Not measuredOnly Llama 3.1 8B Instruct measured
AIME 2025 (Artificial Analysis run)4.3%Not measuredOnly Llama 3.1 8B Instruct measured
OTIS Mock AIME1.7%73.3%o1
FrontierMath, tiers 1 to 3Not measured14.7%Only o1 measured
MATH level 522.9%94.7%o1
GSM8K82.4%Not measuredOnly Llama 3.1 8B Instruct measured
LMArena Text: math11791388o1
LMArena Text: mathematical work11801390o1
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
MMLU ProNot measured83.5%Only o1 measured
LegalBench (Vals AI)Not measured80.4%Only o1 measured
TaxEval (Vals AI)Not measured74.3%Only o1 measured
MedQA (Vals AI)Not measured96.5%Only o1 measured
MMLU Pro (Artificial Analysis run)47.6%84.1%o1
SimpleQA VerifiedNot measured41.1%Only o1 measured
MMLU56.1%Not measuredOnly Llama 3.1 8B Instruct measured
GeoBenchNot measured80.0%Only o1 measured
LMArena Text: science11931369o1
LMArena Text: medicine and healthcare11821355o1
LMArena Text: legal and government12061368o1
LMArena Text: business and finance11661328o1
Neither model has a result on the other 5 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
General benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
IFBench28.6%70.3%o1
Long context reasoning (AA-LCR)18.0%65.0%o1
DTBench50.9%74.7%o1
LMCA5.4%22.3%o1
Fiction.LiveBenchNot measured83.3%Only o1 measured
Creative writing (Lech Mazur)Not measured70.2%Only o1 measured
PIQA81.2%Not measuredOnly Llama 3.1 8B Instruct measured
LMArena Text11871366o1
LMArena Text: instruction following11591367o1
LMArena Text: creative writing11541347o1
LMArena VisionNot measured1168Only o1 measured
LMArena Text: English12181372o1
LMArena Text: non-English11481358o1
LMArena Text: Chinese11511394o1
LMArena Text: German11441337o1
LMArena Text: Japanese10611346o1
LMArena Text: Korean10531396o1
LMArena Text: French11781344o1
LMArena Text: Spanish11691345o1
LMArena Text: Russian11581356o1
LMArena Text: multi-turn11721355o1
LMArena Text: longer queries11811378o1
LMArena Text: writing and language11621360o1
LMArena Text: entertainment and media11451358o1
LMArena Vision: EnglishNot measured1162Only o1 measured
LMArena Vision: ChineseNot measured1235Only o1 measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Llama 3.1 8B Instruct and o1
BenchmarkLlama 3.1 8B Instructo1Leader
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

Llama 3.1 8B Instruct$0.0001Fits in one request
o1$0.045Fits in one request

Llama 3.1 8B Instruct costs less

Repository review

50K input + 3K output tokens

Llama 3.1 8B Instruct$0.0027Fits in one request
o1$0.930Fits in one request

Llama 3.1 8B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.1 8B Instruct$0.011Exceeds the context window
o1$3.60Exceeds the context window

Llama 3.1 8B 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 Llama 3.1 8B Instruct and o1
SpecificationMeta Llama 3.1 8B InstructOpenAI o1
MakerMeta LlamaOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJuly 23, 2024December 17, 2024
Context window131K200K
Input $/Mtok$0.05$15.00
Output $/Mtok$0.08$60.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.1 8B Instruct better than o1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Llama 3.1 8B Instruct has the edge where output tokens cost 750.0x less, and where what matters is AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.

Which is cheaper, Llama 3.1 8B Instruct or o1?

Llama 3.1 8B Instruct costs $0.05 per million input tokens and $0.08 per million output tokens; o1 costs $15.00 and $60.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.1 8B Instruct or o1?

o1, with 200K tokens against 131K.

How many benchmarks is the Llama 3.1 8B Instruct vs o1 comparison based on?

44 benchmarks have a result for both models as of October 21, 2026. Llama 3.1 8B Instruct's coding index rests on 0 independent benchmarks and o1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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