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GPT-4 Turbo vs Llama 3.3 70B Instruct

Llama 3.3 70B Instruct leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 7.7 to 7.0, and Llama 3.3 70B Instruct costs 41.7x less per output token ($0.72 vs $30.00 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace GPT-4 Turbo Replace Llama 3.3 70B Instruct
GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
17
Llama 3.3 70B InstructMeta Llama
Coding
No data
Overall
26.0
Output $/M
$0.72
20
vs boards won of 37 shared

GPT-4 Turbo or Llama 3.3 70B Instruct: which to pick

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

Pick GPT-4 Turbo for work measured by LMArena Text: software and IT or AA Intelligence Index, where it leads.

Model AGPT-4 TurboOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BLlama 3.3 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
GPT-4 Turbo only
5
Llama 3.3 70B Instruct only
15
Like-for-like categories
6 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 Turbo not benchmarked, Llama 3.3 70B Instruct not benchmarked.
Widest category
Knowledge, 4.0 points apart on average over 6 shared benchmarks.
Widest single gap
AA Coding Index: GPT-4 Turbo 21.5 against Llama 3.3 70B Instruct 11.9, 9.6 points apart on a 0 to 100 scale.
Output price
GPT-4 Turbo $30.00 against Llama 3.3 70B Instruct $0.72 per million output tokens, 41.7x apart.
Context window
GPT-4 Turbo takes 128K tokens, Llama 3.3 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 TurboBarsLlama 3.3 70B InstructTies
Coding31
Intelligence02
Reasoning04
Math20
Knowledge06
General127
All shared boards1720
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
Coding benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
AA Coding Index21.511.9GPT-4 Turbo
LiveCodeBench (Artificial Analysis run)29.1%28.8%GPT-4 Turbo
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Llama 3.3 70B Instruct measured
WeirdMLNot measured14.4%Only Llama 3.3 70B Instruct measured
LMArena Text: coding12681268GPT-4 Turbo
LMArena Text: software and IT12671273Llama 3.3 70B Instruct
Neither model has a result on the other 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
AA Intelligence Index7.07.7Llama 3.3 70B Instruct
Epoch Capabilities Index127.3127.3Llama 3.3 70B Instruct
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
τ²-Bench TelecomNot measured26.6%Only Llama 3.3 70B Instruct measured
BALROGNot measured23.0%Only Llama 3.3 70B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)Not measured31.9%Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
GPQA Diamond (Artificial Analysis run)Not measured49.8%Only Llama 3.3 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)3.1%3.6%Llama 3.3 70B Instruct
GPQA Diamond (Epoch AI run)Not measured47.4%Only Llama 3.3 70B Instruct measured
SimpleBenchNot measured19.9%Only Llama 3.3 70B Instruct measured
LMArena Text: hard prompts12511257Llama 3.3 70B Instruct
LMArena Text: expert12231225Llama 3.3 70B Instruct
LMArena Text: hard prompts in English12661277Llama 3.3 70B Instruct
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
AA Math IndexNot measured7.7Only Llama 3.3 70B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured7.7%Only Llama 3.3 70B Instruct measured
OTIS Mock AIMENot measured5.1%Only Llama 3.3 70B Instruct measured
MATH level 5Not measured41.6%Only Llama 3.3 70B Instruct measured
LMArena Text: math12721267GPT-4 Turbo
LMArena Text: mathematical work12681267GPT-4 Turbo
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
Knowledge benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
LegalBench (Vals AI)80.5%Not measuredOnly GPT-4 Turbo measured
MedQA (Vals AI)82.0%Not measuredOnly GPT-4 Turbo measured
MMLU Pro (Artificial Analysis run)69.4%71.3%Llama 3.3 70B Instruct
MMLU81.3%86.3%Llama 3.3 70B Instruct
LMArena Text: science12561284Llama 3.3 70B Instruct
LMArena Text: medicine and healthcare12391275Llama 3.3 70B Instruct
LMArena Text: legal and government12651284Llama 3.3 70B Instruct
LMArena Text: business and finance12221243Llama 3.3 70B Instruct
Neither model has a result on the other 10 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index127
General benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 70B InstructLeader
IFBenchNot measured47.1%Only Llama 3.3 70B Instruct measured
Long context reasoning (AA-LCR)Not measured15.7%Only Llama 3.3 70B Instruct measured
DTBench61.6%59.5%GPT-4 Turbo
LMCA9.8%17.5%Llama 3.3 70B Instruct
Fiction.LiveBenchNot measured33.3%Only Llama 3.3 70B Instruct measured
LMArena Text12721274Llama 3.3 70B Instruct
LMArena Text: instruction following12491242GPT-4 Turbo
LMArena Text: creative writing12681250GPT-4 Turbo
LMArena Vision1090Not measuredOnly GPT-4 Turbo measured
LMArena Text: English12911303Llama 3.3 70B Instruct
LMArena Text: non-English12451236GPT-4 Turbo
LMArena Text: Chinese12421217GPT-4 Turbo
LMArena Text: German12591251GPT-4 Turbo
LMArena Text: Japanese11941150GPT-4 Turbo
LMArena Text: Korean11871142GPT-4 Turbo
LMArena Text: French12761282Llama 3.3 70B Instruct
LMArena Text: Spanish12601269Llama 3.3 70B Instruct
LMArena Text: Russian12591252GPT-4 Turbo
LMArena Text: Polish13021259GPT-4 Turbo
LMArena Text: multi-turn12671280Llama 3.3 70B Instruct
LMArena Text: longer queries12541255Llama 3.3 70B Instruct
LMArena Text: writing and language12791255GPT-4 Turbo
LMArena Text: entertainment and media12581241GPT-4 Turbo
LMArena Vision: English1097Not measuredOnly GPT-4 Turbo measured
LMArena Vision: Chinese1045Not measuredOnly GPT-4 Turbo measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4 Turbo and Llama 3.3 70B Instruct
BenchmarkGPT-4 TurboLlama 3.3 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 Turbo$0.025Fits in one request
Llama 3.3 70B Instruct$0.0008Fits in one request

Llama 3.3 70B Instruct costs less

Repository review

50K input + 3K output tokens

GPT-4 Turbo$0.590Fits in one request
Llama 3.3 70B Instruct$0.025Fits in one request

Llama 3.3 70B Instruct costs less

Agent loop

200K input + 10K output tokens

GPT-4 Turbo$2.30Exceeds the context window
Llama 3.3 70B Instruct$0.097Exceeds the context window

Llama 3.3 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 Turbo and Llama 3.3 70B Instruct
SpecificationOpenAI GPT-4 TurboMeta Llama 3.3 70B Instruct
MakerOpenAIMeta Llama
WeightsNo public weights listedOpen weights
ReleasedApril 9, 2024December 6, 2024
Context window128K131K
Input $/Mtok$10.00$0.45
Output $/Mtok$30.00$0.72
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 Turbo better than Llama 3.3 70B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4 Turbo for work measured by LMArena Text: software and IT or AA Intelligence Index, where it leads.

Which is cheaper, GPT-4 Turbo or Llama 3.3 70B Instruct?

GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Llama 3.3 70B Instruct costs $0.45 and $0.72. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4 Turbo or Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct, with 131K tokens against 128K.

How many benchmarks is the GPT-4 Turbo vs Llama 3.3 70B Instruct comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. GPT-4 Turbo's coding index rests on 0 independent benchmarks and Llama 3.3 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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