Enter opens the highlighted result. Esc closes.

Llama 3.1 70B Instruct vs Qwen3.5-Flash

Qwen3.5-Flash costs 2.2x less per output token than Llama 3.1 70B Instruct ($0.26 vs $0.56 per million). Updated October 22, 2026; 32 benchmarks have a result for both.

Replace Llama 3.1 70B Instruct Replace Qwen3.5-Flash
Llama 3.1 70B InstructMeta Llama
Coding
No data
Overall
24.3
Output $/M
$0.56
0
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
32
vs boards won of 32 shared

Llama 3.1 70B Instruct or Qwen3.5-Flash: which to pick

Only Qwen3.5-Flash has a coding score, 41.1 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.

Model ALlama 3.1 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
32
Llama 3.1 70B Instruct only
15
Qwen3.5-Flash only
23
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
Llama 3.1 70B Instruct not benchmarked, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
Math, 44.4 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: Llama 3.1 70B Instruct 3.6% against Qwen3.5-Flash 84.4%, 80.8 points apart on a 0 to 100 scale.
Output price
Llama 3.1 70B Instruct $0.56 against Qwen3.5-Flash $0.26 per million output tokens, 2.2x apart.
Context window
Llama 3.1 70B Instruct takes 131K tokens, Qwen3.5-Flash 1M.

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 InstructBarsQwen3.5-FlashTies
Coding02
Intelligence01
Reasoning04
Math03
Knowledge04
General018
All shared boards032
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
LiveCodeBench (Artificial Analysis run)23.2%Not measuredOnly Llama 3.1 70B Instruct 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 measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding12601412Qwen3.5-Flash
LMArena Text: software and IT12601416Qwen3.5-Flash
LMArena WebDev: ReactNot measured1229Only Qwen3.5-Flash measured
LMArena WebDev: HTMLNot measured1291Only Qwen3.5-Flash measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
AA Intelligence Index6.6Not measuredOnly Llama 3.1 70B Instruct measured
Epoch Capabilities Index125.9143.5Qwen3.5-Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
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 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)40.9%Not measuredOnly Llama 3.1 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)4.5%Not measuredOnly Llama 3.1 70B Instruct measured
GPQA Diamond (Epoch AI run)44.2%82.3%Qwen3.5-Flash
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts12411403Qwen3.5-Flash
LMArena Text: expert12091407Qwen3.5-Flash
LMArena Text: hard prompts in English12611409Qwen3.5-Flash
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
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%84.4%Qwen3.5-Flash
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
MATH level 536.7%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: math12521407Qwen3.5-Flash
LMArena Text: mathematical work12531413Qwen3.5-Flash
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
MMLU Pro (Artificial Analysis run)67.6%Not measuredOnly Llama 3.1 70B Instruct measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
MMLU80.1%Not measuredOnly Llama 3.1 70B Instruct measured
LMArena Text: science12761415Qwen3.5-Flash
LMArena Text: medicine and healthcare12571407Qwen3.5-Flash
LMArena Text: legal and government12831398Qwen3.5-Flash
LMArena Text: business and finance12351394Qwen3.5-Flash
Neither model has a result on the other 4 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 Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for Llama 3.1 70B Instruct and Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
IFBench34.4%Not measuredOnly Llama 3.1 70B Instruct measured
DTBench60.0%82.9%Qwen3.5-Flash
LMCA14.8%29.1%Qwen3.5-Flash
LMArena Text12611397Qwen3.5-Flash
LMArena Text: instruction following12311374Qwen3.5-Flash
LMArena Text: creative writing12321343Qwen3.5-Flash
LMArena Text: English12941404Qwen3.5-Flash
LMArena Text: non-English12191385Qwen3.5-Flash
LMArena Text: Chinese12151445Qwen3.5-Flash
LMArena Text: German12221390Qwen3.5-Flash
LMArena Text: Japanese11321369Qwen3.5-Flash
LMArena Text: Korean11401344Qwen3.5-Flash
LMArena Text: French12621413Qwen3.5-Flash
LMArena Text: Spanish12531400Qwen3.5-Flash
LMArena Text: Russian12341380Qwen3.5-Flash
LMArena Text: PolishNot measured1376Only Qwen3.5-Flash measured
LMArena Text: multi-turn12561393Qwen3.5-Flash
LMArena Text: longer queries12411392Qwen3.5-Flash
LMArena Text: writing and language12361369Qwen3.5-Flash
LMArena Text: entertainment and media12301347Qwen3.5-Flash
Neither model has a result on the other 24 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 Qwen3.5-Flash
BenchmarkLlama 3.1 70B InstructQwen3.5-FlashLeader
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
Qwen3.5-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Llama 3.1 70B Instruct$0.030Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Llama 3.1 70B Instruct$0.118Exceeds the context window
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-Flash 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 Qwen3.5-Flash
SpecificationMeta Llama 3.1 70B InstructQwen3.5-Flash
MakerMeta LlamaQwen
WeightsOpen weightsNo public weights listed
ReleasedJuly 23, 2024February 25, 2026
Context window131K1M
Input $/Mtok$0.56$0.065
Output $/Mtok$0.56$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it02
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.1 70B Instruct better than Qwen3.5-Flash for coding?

Only Qwen3.5-Flash has a coding score, 41.1 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 Qwen3.5-Flash?

Llama 3.1 70B Instruct costs $0.56 per million input tokens and $0.56 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

Which has the bigger context window, Llama 3.1 70B Instruct or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 131K.

How many benchmarks is the Llama 3.1 70B Instruct vs Qwen3.5-Flash comparison based on?

32 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 Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next