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Grok Build 0.1 vs Llama 3.1 70B Instruct

Grok Build 0.1 leads Llama 3.1 70B Instruct on the Artificial Analysis Intelligence Index, 27.2 to 6.6, and Llama 3.1 70B Instruct costs 3.6x less per output token ($0.56 vs $2.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.

Grok Build 0.1xAI
Coding
No data
Overall
No data
Output $/M
$2.00
1
Llama 3.1 70B InstructMeta Llama
Coding
No data
Overall
24.3
Output $/M
$0.56
0
vs boards won of 1 shared

Grok Build 0.1 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 Grok Build 0.1 for a larger context window (256K against 131K tokens).

Shared results
1
Grok Build 0.1 only
2
Llama 3.1 70B Instruct only
46
Like-for-like categories
1 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
Grok Build 0.1 not benchmarked, Llama 3.1 70B Instruct not benchmarked.
Widest category
Intelligence, 20.6 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: Grok Build 0.1 27.2 against Llama 3.1 70B Instruct 6.6, 20.6 points apart on a 0 to 100 scale.
Output price
Grok Build 0.1 $2.00 against Llama 3.1 70B Instruct $0.56 per million output tokens, 3.6x apart.
Context window
Grok Build 0.1 takes 256K 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
CategoryGrok Build 0.1BarsLlama 3.1 70B InstructTies
Intelligence10
All shared boards10
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
Coding benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
AA Coding Index51.5Not measuredOnly Grok Build 0.1 measured
Vibe Code Bench (Vals AI)13.4%Not measuredOnly Grok Build 0.1 measured
LiveCodeBench (Artificial Analysis run)Not measured23.2%Only Llama 3.1 70B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Llama 3.1 70B Instruct measured
WeirdMLNot measured9.0%Only Llama 3.1 70B Instruct measured
LMArena Text: codingNot measured1260Only Llama 3.1 70B Instruct measured
LMArena Text: software and ITNot measured1260Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
AA Intelligence Index27.26.6Grok Build 0.1
Epoch Capabilities IndexNot measured125.9Only Llama 3.1 70B Instruct measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
τ²-Bench TelecomNot measured15.2%Only Llama 3.1 70B Instruct measured
BALROGNot measured27.9%Only Llama 3.1 70B Instruct measured
TheAgentCompanyNot measured6.9%Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 38 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Reasoning benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
GPQA Diamond (Artificial Analysis run)Not measured40.9%Only Llama 3.1 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.5%Only Llama 3.1 70B Instruct measured
GPQA Diamond (Epoch AI run)Not measured44.2%Only Llama 3.1 70B Instruct measured
LMArena Text: hard promptsNot measured1241Only Llama 3.1 70B Instruct measured
LMArena Text: expertNot measured1209Only Llama 3.1 70B Instruct measured
LMArena Text: hard prompts in EnglishNot measured1261Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
AA Math IndexNot measured4.0Only Llama 3.1 70B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured4.0%Only Llama 3.1 70B Instruct measured
OTIS Mock AIMENot measured3.6%Only Llama 3.1 70B Instruct measured
MATH level 5Not measured36.7%Only Llama 3.1 70B Instruct measured
LMArena Text: mathNot measured1252Only Llama 3.1 70B Instruct measured
LMArena Text: mathematical workNot measured1253Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
MMLU Pro (Artificial Analysis run)Not measured67.6%Only Llama 3.1 70B Instruct measured
MMLUNot measured80.1%Only Llama 3.1 70B Instruct measured
LMArena Text: scienceNot measured1276Only Llama 3.1 70B Instruct measured
LMArena Text: medicine and healthcareNot measured1257Only Llama 3.1 70B Instruct measured
LMArena Text: legal and governmentNot measured1283Only Llama 3.1 70B Instruct measured
LMArena Text: business and financeNot measured1235Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 12 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
General benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 3.1 70B InstructLeader
IFBenchNot measured34.4%Only Llama 3.1 70B Instruct measured
DTBenchNot measured60.0%Only Llama 3.1 70B Instruct measured
LMCANot measured14.8%Only Llama 3.1 70B Instruct measured
LMArena TextNot measured1261Only Llama 3.1 70B Instruct measured
LMArena Text: instruction followingNot measured1231Only Llama 3.1 70B Instruct measured
LMArena Text: creative writingNot measured1232Only Llama 3.1 70B Instruct measured
LMArena Text: EnglishNot measured1294Only Llama 3.1 70B Instruct measured
LMArena Text: non-EnglishNot measured1219Only Llama 3.1 70B Instruct measured
LMArena Text: ChineseNot measured1215Only Llama 3.1 70B Instruct measured
LMArena Text: GermanNot measured1222Only Llama 3.1 70B Instruct measured
LMArena Text: JapaneseNot measured1132Only Llama 3.1 70B Instruct measured
LMArena Text: KoreanNot measured1140Only Llama 3.1 70B Instruct measured
LMArena Text: FrenchNot measured1262Only Llama 3.1 70B Instruct measured
LMArena Text: SpanishNot measured1253Only Llama 3.1 70B Instruct measured
LMArena Text: RussianNot measured1234Only Llama 3.1 70B Instruct measured
LMArena Text: multi-turnNot measured1256Only Llama 3.1 70B Instruct measured
LMArena Text: longer queriesNot measured1241Only Llama 3.1 70B Instruct measured
LMArena Text: writing and languageNot measured1236Only Llama 3.1 70B Instruct measured
LMArena Text: entertainment and mediaNot measured1230Only Llama 3.1 70B Instruct measured
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Grok Build 0.1 and Llama 3.1 70B Instruct
BenchmarkGrok Build 0.1Llama 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

Grok Build 0.1$0.0020Fits 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

Grok Build 0.1$0.056Fits 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

Grok Build 0.1$0.220Fits 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 Grok Build 0.1 and Llama 3.1 70B Instruct
SpecificationSpaceXAI Grok Build 0.1Meta Llama 3.1 70B Instruct
MakerxAIMeta Llama
WeightsNo public weights listedOpen weights
ReleasedMay 20, 2026July 23, 2024
Context window256K131K
Input $/Mtok$1.00$0.56
Output $/Mtok$2.00$0.56
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Grok Build 0.1 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 Grok Build 0.1 for a larger context window (256K against 131K tokens).

Which is cheaper, Grok Build 0.1 or Llama 3.1 70B Instruct?

Grok Build 0.1 costs $1.00 per million input tokens and $2.00 per million output tokens; Llama 3.1 70B Instruct costs $0.56 and $0.56. Cost per solved task is known for neither of them.

Which has the bigger context window, Grok Build 0.1 or Llama 3.1 70B Instruct?

Grok Build 0.1, with 256K tokens against 131K.

How many benchmarks is the Grok Build 0.1 vs Llama 3.1 70B Instruct comparison based on?

1 benchmarks have a result for both models as of October 22, 2026. Grok Build 0.1's coding index rests on 1 independent benchmark 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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