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GPT-4.1 vs Llama 3.1 70B Instruct

GPT-4.1 leads Llama 3.1 70B Instruct on the Artificial Analysis Intelligence Index, 12.7 to 6.6, and Llama 3.1 70B Instruct costs 14.3x less per output token ($0.56 vs $8.00 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace GPT-4.1 Replace Llama 3.1 70B Instruct
GPT-4.1OpenAI
Coding
No data
Overall
36.5
Output $/M
$8.00
43
Llama 3.1 70B InstructMeta Llama
Coding
No data
Overall
24.3
Output $/M
$0.56
1
vs boards won of 44 shared

GPT-4.1 or Llama 3.1 70B Instruct: which to pick

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

Pick GPT-4.1 for a larger context window (1.05M against 131K tokens) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.

Model AGPT-4.1OpenAINot benchmarkedNo coding benchmark$0.37 per solved taskModel BLlama 3.1 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
44
GPT-4.1 only
48
Llama 3.1 70B Instruct only
3
Like-for-like categories
7 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
GPT-4.1 not benchmarked, Llama 3.1 70B Instruct not benchmarked.
Widest category
Agentic work, 31.9 points apart on average over 1 shared benchmark.
Widest single gap
MATH level 5: GPT-4.1 83.0% against Llama 3.1 70B Instruct 36.7%, 46.3 points apart on a 0 to 100 scale.
Output price
GPT-4.1 $8.00 against Llama 3.1 70B Instruct $0.56 per million output tokens, 14.3x apart.
Context window
GPT-4.1 takes 1.05M tokens, Llama 3.1 70B Instruct 131K.

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
CategoryGPT-4.1BarsLlama 3.1 70B InstructTies
Coding50
Intelligence20
Agentic work10
Reasoning51
Math60
Knowledge50
General190
All shared boards431
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
Aider polyglot52.4%Not measuredOnly GPT-4.1 measured
SWE-bench Verified39.6%Not measuredOnly GPT-4.1 measured
SWE-bench Multimodal31.1%Not measuredOnly GPT-4.1 measured
LiveCodeBench (Vals AI)54.7%Not measuredOnly GPT-4.1 measured
LiveCodeBench (Artificial Analysis run)45.7%23.2%GPT-4.1
Terminal-Bench Hard (Artificial Analysis run)13.6%3.0%GPT-4.1
WeirdML39.0%9.0%GPT-4.1
ALE-Bench558.1Not measuredOnly GPT-4.1 measured
LMArena Text: coding13901260GPT-4.1
LMArena Text: software and IT13911260GPT-4.1
SciCode4.6%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
AA Intelligence Index12.76.6GPT-4.1
Epoch Capabilities Index136.7125.9GPT-4.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
τ²-Bench Telecom47.1%15.2%GPT-4.1
BALROGNot measured27.9%Only Llama 3.1 70B Instruct measured
TheAgentCompanyNot measured6.9%Only Llama 3.1 70B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)54.0%Not measuredOnly GPT-4.1 measured
BrowseComp-Plus36.4%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
GPQA Diamond65.4%Not measuredOnly GPT-4.1 measured
MMMU Pro (Vals AI)72.4%Not measuredOnly GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)66.6%40.9%GPT-4.1
Humanity's Last Exam (Artificial Analysis run)4.2%4.5%Llama 3.1 70B Instruct
GPQA Diamond (Epoch AI run)66.9%44.2%GPT-4.1
ARC-AGI5.5%Not measuredOnly GPT-4.1 measured
ARC-AGI-20.4%Not measuredOnly GPT-4.1 measured
SimpleBench27.0%Not measuredOnly GPT-4.1 measured
Chess puzzles3.0%Not measuredOnly GPT-4.1 measured
LMArena Text: hard prompts13841241GPT-4.1
LMArena Text: expert13641209GPT-4.1
LMArena Text: hard prompts in English13931261GPT-4.1
LMArena Vision: diagrams1215Not measuredOnly GPT-4.1 measured
LMArena Vision: homework1248Not measuredOnly GPT-4.1 measured
Kagi LLM Benchmark52.3%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
AIME39.6%Not measuredOnly GPT-4.1 measured
MATH 500 (Vals AI)87.2%Not measuredOnly GPT-4.1 measured
MGSM (Vals AI)87.7%Not measuredOnly GPT-4.1 measured
AA Math Index34.74.0GPT-4.1
AIME 2025 (Artificial Analysis run)34.7%4.0%GPT-4.1
OTIS Mock AIME38.3%3.6%GPT-4.1
FrontierMath, tiers 1 to 36.0%Not measuredOnly GPT-4.1 measured
MATH level 583.0%36.7%GPT-4.1
LMArena Text: math13691252GPT-4.1
LMArena Text: mathematical work13601253GPT-4.1
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
MMLU Pro80.5%Not measuredOnly GPT-4.1 measured
LegalBench (Vals AI)83.1%Not measuredOnly GPT-4.1 measured
CaseLaw (Vals AI)69.9%Not measuredOnly GPT-4.1 measured
CorpFin (Vals AI)63.0%Not measuredOnly GPT-4.1 measured
TaxEval (Vals AI)75.1%Not measuredOnly GPT-4.1 measured
MortgageTax (Vals AI)65.9%Not measuredOnly GPT-4.1 measured
MedQA (Vals AI)91.2%Not measuredOnly GPT-4.1 measured
MMLU Pro (Artificial Analysis run)80.6%67.6%GPT-4.1
SimpleQA Verified31.1%Not measuredOnly GPT-4.1 measured
MMLUNot measured80.1%Only Llama 3.1 70B Instruct measured
GeoBench72.0%Not measuredOnly GPT-4.1 measured
LMArena Text: science13821276GPT-4.1
LMArena Text: medicine and healthcare13791257GPT-4.1
LMArena Text: legal and government13991283GPT-4.1
LMArena Text: business and finance13691235GPT-4.1
FACTS Benchmark Suite45.8%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
Design Arena: websites1038Not measuredOnly GPT-4.1 measured
Design Arena: UI components997Not measuredOnly GPT-4.1 measured
Design Arena: game dev1079Not measuredOnly GPT-4.1 measured
Design Arena: data viz1104Not measuredOnly GPT-4.1 measured
Design Arena: 3D849Not measuredOnly GPT-4.1 measured
Design Arena: all code categories1025Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B InstructLeader
IFBench43.0%34.4%GPT-4.1
Long context reasoning (AA-LCR)68.3%Not measuredOnly GPT-4.1 measured
DTBench68.3%60.0%GPT-4.1
LMCA25.6%14.8%GPT-4.1
Fiction.LiveBench63.9%Not measuredOnly GPT-4.1 measured
LMArena Text13831261GPT-4.1
LMArena Text: instruction following13671231GPT-4.1
LMArena Text: creative writing13631232GPT-4.1
LMArena Vision1210Not measuredOnly GPT-4.1 measured
LMArena Text: English13921294GPT-4.1
LMArena Text: non-English13701219GPT-4.1
LMArena Text: Chinese13821215GPT-4.1
LMArena Text: German13811222GPT-4.1
LMArena Text: Japanese13191132GPT-4.1
LMArena Text: Korean13381140GPT-4.1
LMArena Text: French13821262GPT-4.1
LMArena Text: Spanish13761253GPT-4.1
LMArena Text: Russian13771234GPT-4.1
LMArena Text: Polish1389Not measuredOnly GPT-4.1 measured
LMArena Text: multi-turn13971256GPT-4.1
LMArena Text: longer queries13851241GPT-4.1
LMArena Text: writing and language13711236GPT-4.1
LMArena Text: entertainment and media13651230GPT-4.1
LMArena Vision: English1209Not measuredOnly GPT-4.1 measured
LMArena Vision: Chinese1226Not measuredOnly GPT-4.1 measured
LMArena Vision: reading text1218Not measuredOnly GPT-4.1 measured
LMArena Vision: humor1196Not measuredOnly GPT-4.1 measured
LMArena Vision: captioning1207Not measuredOnly GPT-4.1 measured
LMArena Vision: recognizing things1208Not measuredOnly GPT-4.1 measured
LMArena Vision: creative writing1210Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 and Llama 3.1 70B Instruct
BenchmarkGPT-4.1Llama 3.1 70B 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

GPT-4.1$0.0060Fits in one request
Llama 3.1 70B Instruct$0.0008Fits in one request

Llama 3.1 70B Instruct costs less

Repository review

50K input + 3K output tokens

GPT-4.1$0.124Fits in one request
Llama 3.1 70B Instruct$0.030Fits in one request

Llama 3.1 70B Instruct costs less

Agent loop

200K input + 10K output tokens

GPT-4.1$0.480Fits in one request
Llama 3.1 70B Instruct$0.118Exceeds the context window

Llama 3.1 70B 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 GPT-4.1 and Llama 3.1 70B Instruct
SpecificationOpenAI GPT-4.1Meta Llama 3.1 70B Instruct
MakerOpenAIMeta Llama
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025July 23, 2024
Context window1.05M131K
Input $/Mtok$2.00$0.56
Output $/Mtok$8.00$0.56
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$0.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 better than Llama 3.1 70B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 for a larger context window (1.05M against 131K tokens) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, GPT-4.1 or Llama 3.1 70B Instruct?

GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Llama 3.1 70B Instruct costs $0.56 and $0.56. Cost per solved task is known for GPT-4.1 only.

Which has the bigger context window, GPT-4.1 or Llama 3.1 70B Instruct?

GPT-4.1, with 1.05M tokens against 131K.

How many benchmarks is the GPT-4.1 vs Llama 3.1 70B Instruct comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. GPT-4.1's coding index rests on 0 independent benchmarks and Llama 3.1 70B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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