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Llama 3.1 70B Instruct vs Nemotron 3.5 Lightning

Nemotron 3.5 Lightning leads Llama 3.1 70B Instruct on the Artificial Analysis Intelligence Index, 12.9 to 6.6, and Nemotron 3.5 Lightning costs 3.8x less per output token ($0.147 vs $0.56 per million). Updated October 22, 2026; 3 benchmarks have a result for both.

Llama 3.1 70B InstructMeta Llama
Coding
No data
Overall
24.3
Output $/M
$0.56
0
Nemotron 3.5 LightningNVIDIA
Coding
22.6
Overall
No data
Output $/M
$0.147
3
vs boards won of 3 shared

Llama 3.1 70B Instruct or Nemotron 3.5 Lightning: which to pick

Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Llama 3.1 70B Instruct has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
3
Llama 3.1 70B Instruct only
44
Nemotron 3.5 Lightning only
17
Like-for-like categories
2 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
Llama 3.1 70B Instruct not benchmarked, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
Widest category
Reasoning, 19.8 points apart on average over 2 shared benchmarks.
Widest single gap
GPQA Diamond (Artificial Analysis run): Llama 3.1 70B Instruct 40.9% against Nemotron 3.5 Lightning 74.3%, 33.4 points apart on a 0 to 100 scale.
Output price
Llama 3.1 70B Instruct $0.56 against Nemotron 3.5 Lightning $0.147 per million output tokens, 3.8x apart.
Context window
Llama 3.1 70B Instruct takes 131K tokens, Nemotron 3.5 Lightning 262K.

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 70B InstructBarsNemotron 3.5 LightningTies
Intelligence01
Reasoning02
All shared boards03
CodingDirectional onlySix of these boards feed the Vibe Coding Index14 boards, none shared
Coding benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
AA Coding IndexNot measured26.8Only Nemotron 3.5 Lightning measured
SWE-bench Verified (Vals AI)Not measured52.8%Only Nemotron 3.5 Lightning measured
Vibe Code Bench (Vals AI)Not measured0.0%Only Nemotron 3.5 Lightning measured
Code migration (Vals AI)Not measured3.0%Only Nemotron 3.5 Lightning measured
ProgramBench (Vals AI)Not measured0.0%Only Nemotron 3.5 Lightning measured
Terminal-Bench 2.1 (Vals AI)Not measured10.9%Only Nemotron 3.5 Lightning measured
CyberBench (Vals AI)Not measured29.5%Only Nemotron 3.5 Lightning measured
LiveCodeBench (Artificial Analysis run)23.2%Not measuredOnly Llama 3.1 70B Instruct measured
SciCodeNot measured32.1%Only Nemotron 3.5 Lightning measured
Terminal-Bench Hard (Artificial Analysis run)3.0%Not measuredOnly Llama 3.1 70B Instruct measured
WeirdML9.0%Not measuredOnly Llama 3.1 70B Instruct measured
ALE-BenchNot measured769.2Only Nemotron 3.5 Lightning measured
LMArena Text: coding1260Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: software and IT1260Not measuredOnly Llama 3.1 70B Instruct measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
AA Intelligence Index6.612.9Nemotron 3.5 Lightning
Epoch Capabilities Index125.9Not measuredOnly Llama 3.1 70B Instruct measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Agentic work benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
AA Agentic IndexNot measured3.5Only Nemotron 3.5 Lightning measured
Finance Agent (Vals AI)Not measured18.5%Only Nemotron 3.5 Lightning measured
Tax Agent Bench (Vals AI)Not measured2.6%Only Nemotron 3.5 Lightning measured
Legal Research Bench (Vals AI)Not measured2.9%Only Nemotron 3.5 Lightning measured
Excel Modeling Benchmark (Vals AI)Not measured17.0%Only Nemotron 3.5 Lightning measured
τ²-Bench Telecom15.2%Not measuredOnly Llama 3.1 70B Instruct measured
BALROG27.9%Not measuredOnly Llama 3.1 70B Instruct measured
TheAgentCompany6.9%Not measuredOnly Llama 3.1 70B Instruct measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
GPQA Diamond (Artificial Analysis run)40.9%74.3%Nemotron 3.5 Lightning
Humanity's Last Exam (Artificial Analysis run)4.5%10.6%Nemotron 3.5 Lightning
GPQA Diamond (Epoch AI run)44.2%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: hard prompts1241Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: expert1209Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: hard prompts in English1261Not measuredOnly 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 Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
AA Math Index4.0Not measuredOnly Llama 3.1 70B Instruct measured
AIME 2025 (Artificial Analysis run)4.0%Not measuredOnly Llama 3.1 70B Instruct measured
OTIS Mock AIME3.6%Not measuredOnly Llama 3.1 70B Instruct measured
MATH level 536.7%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: math1252Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: mathematical work1253Not measuredOnly 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 index7 boards, none shared
Knowledge benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
CorpFin (Vals AI)Not measured54.2%Only Nemotron 3.5 Lightning measured
MMLU Pro (Artificial Analysis run)67.6%Not measuredOnly Llama 3.1 70B Instruct measured
MMLU80.1%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: science1276Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: medicine and healthcare1257Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: legal and government1283Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: business and finance1235Not measuredOnly Llama 3.1 70B Instruct measured
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
General benchmarks for Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
MedScribe (Vals AI)Not measured4.3%Only Nemotron 3.5 Lightning measured
IFBench34.4%Not measuredOnly Llama 3.1 70B Instruct measured
Long context reasoning (AA-LCR)Not measured60.3%Only Nemotron 3.5 Lightning measured
DTBench60.0%Not measuredOnly Llama 3.1 70B Instruct measured
LMCA14.8%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text1261Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: instruction following1231Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: creative writing1232Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: English1294Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: non-English1219Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: Chinese1215Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: German1222Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: Japanese1132Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: Korean1140Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: French1262Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: Spanish1253Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: Russian1234Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: multi-turn1256Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: longer queries1241Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: writing and language1236Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: entertainment and media1230Not measuredOnly Llama 3.1 70B Instruct measured
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 Llama 3.1 70B Instruct and Nemotron 3.5 Lightning
BenchmarkLlama 3.1 70B InstructNemotron 3.5 LightningLeader
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 70B Instruct$0.0008Fits in one request
Nemotron 3.5 Lightning$0.0001Fits in one request

Nemotron 3.5 Lightning costs less

Repository review

50K input + 3K output tokens

Llama 3.1 70B Instruct$0.030Fits in one request
Nemotron 3.5 Lightning$0.0031Fits in one request

Nemotron 3.5 Lightning costs less

Agent loop

200K input + 10K output tokens

Llama 3.1 70B Instruct$0.118Exceeds the context window
Nemotron 3.5 Lightning$0.012Fits in one request

Nemotron 3.5 Lightning 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 70B Instruct and Nemotron 3.5 Lightning
SpecificationMeta Llama 3.1 70B InstructNVIDIA Nemotron 3.5 Lightning
MakerMeta LlamaNVIDIA
WeightsOpen weightsOpen weights
ReleasedJuly 23, 2024August 11, 2026
Context window131K262K
Input $/Mtok$0.56$0.0534
Output $/Mtok$0.56$0.147
Coding indexNot benchmarked22.6
Independent measurements behind it02
Cost per solved taskNot computable$0.06
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.1 70B Instruct better than Nemotron 3.5 Lightning for coding?

Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Llama 3.1 70B Instruct has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Llama 3.1 70B Instruct or Nemotron 3.5 Lightning?

Llama 3.1 70B Instruct costs $0.56 per million input tokens and $0.56 per million output tokens; Nemotron 3.5 Lightning costs $0.0534 and $0.147. Cost per solved task is known for Nemotron 3.5 Lightning only.

Which has the bigger context window, Llama 3.1 70B Instruct or Nemotron 3.5 Lightning?

Nemotron 3.5 Lightning, with 262K tokens against 131K.

How many benchmarks is the Llama 3.1 70B Instruct vs Nemotron 3.5 Lightning comparison based on?

3 benchmarks have a result for both models as of October 22, 2026. Llama 3.1 70B Instruct's coding index rests on 0 independent benchmarks and Nemotron 3.5 Lightning's on 2. Where only one model has a result, the page says so instead of naming a winner.

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