Llama 3.1 8B Instruct vs Qwen3.6 Flash
Llama 3.1 8B Instruct costs 14.1x less per output token than Qwen3.6 Flash ($0.08 vs $1.125 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Llama 3.1 8B Instruct or Qwen3.6 Flash: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama 3.1 8B Instruct for output tokens 14.1x cheaper ($0.08 vs $1.125 per million) and work measured by Epoch Capabilities Index or GPQA Diamond (Epoch AI run), where it leads.
- Shared results
- 5
- Llama 3.1 8B Instruct only
- 46
- Qwen3.6 Flash only
- 6
- Like-for-like categories
- 4 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Llama 3.1 8B Instruct has a AA Intelligence Index result, 6.9.
Directional only
Long documents
Listed context window
Qwen3.6 Flash
Qwen3.6 Flash takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.1 8B Instruct
Llama 3.1 8B Instruct $0.0001, Qwen3.6 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- Llama 3.1 8B Instruct not benchmarked, Qwen3.6 Flash not benchmarked.
- Widest category
- Math, 82.8 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: Llama 3.1 8B Instruct 1.7% against Qwen3.6 Flash 84.4%, 82.8 points apart on a 0 to 100 scale.
- Output price
- Llama 3.1 8B Instruct $0.08 against Qwen3.6 Flash $1.125 per million output tokens, 14.1x apart.
- Context window
- Llama 3.1 8B Instruct takes 131K tokens, Qwen3.6 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.
| Category | Llama 3.1 8B Instruct | Bars | Qwen3.6 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Math | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 5 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AA Coding Index | 5.4 | Not measured | Only Llama 3.1 8B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | 11.6% | Not measured | Only Llama 3.1 8B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | Not measured | Only Llama 3.1 8B Instruct measured |
| WeirdML | 1.7% | Not measured | Only Llama 3.1 8B Instruct measured |
| ALE-Bench | Not measured | 326.4 | Only Qwen3.6 Flash measured |
| LMArena Text: coding | 1195 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: software and IT | 1195 | Not measured | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.9 | Not measured | Only Llama 3.1 8B Instruct measured |
| Epoch Capabilities Index | 116.5 | 142.9 | Qwen3.6 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 16.4% | Not measured | Only Llama 3.1 8B Instruct measured |
| BALROG | 15.1% | Not measured | Only Llama 3.1 8B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | 25.8% | Not measured | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 25.9% | Not measured | Only Llama 3.1 8B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 5.3% | Not measured | Only Llama 3.1 8B Instruct measured |
| GPQA Diamond (Epoch AI run) | 27.0% | 83.3% | Qwen3.6 Flash |
| SimpleBench | Not measured | 35.2% | Only Qwen3.6 Flash measured |
| Chess puzzles | Not measured | 12.0% | Only Qwen3.6 Flash measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.6 Flash measured |
| LMArena Text: hard prompts | 1175 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: expert | 1144 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: hard prompts in English | 1196 | Not measured | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AA Math Index | 4.3 | Not measured | Only Llama 3.1 8B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 4.3% | Not measured | Only Llama 3.1 8B Instruct measured |
| OTIS Mock AIME | 1.7% | 84.4% | Qwen3.6 Flash |
| FrontierMath, tiers 1 to 3 | Not measured | 22.5% | Only Qwen3.6 Flash measured |
| MATH level 5 | 22.9% | Not measured | Only Llama 3.1 8B Instruct measured |
| GSM8K | 82.4% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: math | 1179 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: mathematical work | 1180 | Not measured | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 47.6% | Not measured | Only Llama 3.1 8B Instruct measured |
| SimpleQA Verified | Not measured | 15.9% | Only Qwen3.6 Flash measured |
| MMLU | 56.1% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: science | 1193 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: medicine and healthcare | 1182 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: legal and government | 1206 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: business and finance | 1166 | Not measured | Only Llama 3.1 8B 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
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| IFBench | 28.6% | Not measured | Only Llama 3.1 8B Instruct measured |
| Long context reasoning (AA-LCR) | 18.0% | Not measured | Only Llama 3.1 8B Instruct measured |
| DTBench | 50.9% | 77.1% | Qwen3.6 Flash |
| LMCA | 5.4% | 31.0% | Qwen3.6 Flash |
| PIQA | 81.2% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text | 1187 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: instruction following | 1159 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: creative writing | 1154 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: English | 1218 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: non-English | 1148 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Chinese | 1151 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: German | 1144 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Japanese | 1061 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Korean | 1053 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: French | 1178 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Spanish | 1169 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: Russian | 1158 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: multi-turn | 1172 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: longer queries | 1181 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: writing and language | 1162 | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: entertainment and media | 1145 | Not measured | Only Llama 3.1 8B 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
| Benchmark | Llama 3.1 8B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| 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 8B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.1 8B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.1 8B 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.
| Specification | Meta Llama 3.1 8B Instruct | Qwen3.6 Flash |
|---|---|---|
| Maker | Meta Llama | Qwen |
| Weights | Open weights | No public weights listed |
| Released | July 23, 2024 | April 27, 2026 |
| Context window | 131K | 1M |
| Input $/Mtok | $0.05 | $0.1875 |
| Output $/Mtok | $0.08 | $1.125 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.1 8B Instruct better than Qwen3.6 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.1 8B Instruct for output tokens 14.1x cheaper ($0.08 vs $1.125 per million) and work measured by Epoch Capabilities Index or GPQA Diamond (Epoch AI run), where it leads.
Which is cheaper, Llama 3.1 8B Instruct or Qwen3.6 Flash?
Llama 3.1 8B Instruct costs $0.05 per million input tokens and $0.08 per million output tokens; Qwen3.6 Flash costs $0.1875 and $1.125. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.1 8B Instruct or Qwen3.6 Flash?
Qwen3.6 Flash, with 1M tokens against 131K.
How many benchmarks is the Llama 3.1 8B Instruct vs Qwen3.6 Flash comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Llama 3.1 8B Instruct's coding index rests on 0 independent benchmarks and Qwen3.6 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.