Llama 3.3 70B Instruct vs Qwen3.5 Plus 2026-04-20
Llama 3.3 70B Instruct costs 2.5x less per output token than Qwen3.5 Plus 2026-04-20 ($0.72 vs $1.80 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Llama 3.3 70B Instruct or Qwen3.5 Plus 2026-04-20: which to pick
Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding.
Pick Llama 3.3 70B Instruct for output tokens 2.5x cheaper ($0.72 vs $1.80 per million).
- Shared results
- 5
- Llama 3.3 70B Instruct only
- 47
- Qwen3.5 Plus 2026-04-20 only
- 20
- 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
Only Qwen3.5 Plus 2026-04-20 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Llama 3.3 70B Instruct has a AA Intelligence Index result, 7.7.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5 Plus 2026-04-20 has a GPQA Diamond result, 87.4%.
Directional only
Math
AIME
No call
Only Qwen3.5 Plus 2026-04-20 has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5 Plus 2026-04-20 has a MMLU Pro result, 87.2%.
Directional only
Long documents
Listed context window
Qwen3.5 Plus 2026-04-20
Qwen3.5 Plus 2026-04-20 takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.3 70B Instruct
Llama 3.3 70B Instruct $0.0008, Qwen3.5 Plus 2026-04-20 $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5 Plus 2026-04-20 has the number, $1.35.
Directional only
At a glance
- Coding index
- Llama 3.3 70B Instruct not benchmarked, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
- Widest category
- Math, 81.5 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: Llama 3.3 70B Instruct 5.1% against Qwen3.5 Plus 2026-04-20 86.7%, 81.5 points apart on a 0 to 100 scale.
- Output price
- Llama 3.3 70B Instruct $0.72 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 2.5x apart.
- Context window
- Llama 3.3 70B Instruct takes 131K tokens, Qwen3.5 Plus 2026-04-20 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 3.3 70B Instruct | Bars | Qwen3.5 Plus 2026-04-20 | 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 Index10 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Coding Index | 11.9 | Not measured | Only Llama 3.3 70B Instruct measured |
| LiveCodeBench (Vals AI) | Not measured | 85.3% | Only Qwen3.5 Plus 2026-04-20 measured |
| SWE-bench Verified (Vals AI) | Not measured | 71.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| Vibe Code Bench (Vals AI) | Not measured | 15.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| LiveCodeBench (Artificial Analysis run) | 28.8% | Not measured | Only Llama 3.3 70B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.0% | Not measured | Only Llama 3.3 70B Instruct measured |
| WeirdML | 14.4% | Not measured | Only Llama 3.3 70B Instruct measured |
| ALE-Bench | Not measured | 608.9 | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text: coding | 1268 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: software and IT | 1273 | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | Not measured | Only Llama 3.3 70B Instruct measured |
| Epoch Capabilities Index | 127.3 | 146.2 | Qwen3.5 Plus 2026-04-20 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 26.6% | Not measured | Only Llama 3.3 70B Instruct measured |
| BALROG | 23.0% | Not measured | Only Llama 3.3 70B Instruct measured |
| Vending-Bench 2 | Not measured | $1 | Only Qwen3.5 Plus 2026-04-20 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 31.9% | Not measured | 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 index01
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 87.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMMU Pro (Vals AI) | Not measured | 22.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| GPQA Diamond (Artificial Analysis run) | 49.8% | Not measured | Only Llama 3.3 70B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.6% | Not measured | Only Llama 3.3 70B Instruct measured |
| GPQA Diamond (Epoch AI run) | 47.4% | 84.8% | Qwen3.5 Plus 2026-04-20 |
| SimpleBench | 19.9% | Not measured | Only Llama 3.3 70B Instruct measured |
| Chess puzzles | Not measured | 8.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text: hard prompts | 1257 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: expert | 1225 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: hard prompts in English | 1277 | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| AA Math Index | 7.7 | Not measured | Only Llama 3.3 70B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 7.7% | Not measured | Only Llama 3.3 70B Instruct measured |
| OTIS Mock AIME | 5.1% | 86.7% | Qwen3.5 Plus 2026-04-20 |
| MATH level 5 | 41.6% | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: math | 1267 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: mathematical work | 1267 | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only Qwen3.5 Plus 2026-04-20 measured |
| CaseLaw (Vals AI) | Not measured | 59.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only Qwen3.5 Plus 2026-04-20 measured |
| MortgageTax (Vals AI) | Not measured | 60.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| MedQA (Vals AI) | Not measured | 95.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMLU Pro (Artificial Analysis run) | 71.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| SimpleQA Verified | Not measured | 25.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMLU | 86.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: science | 1284 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: medicine and healthcare | 1275 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: legal and government | 1284 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: business and finance | 1243 | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 7 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 30.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| IFBench | 47.1% | Not measured | Only Llama 3.3 70B Instruct measured |
| Long context reasoning (AA-LCR) | 15.7% | Not measured | Only Llama 3.3 70B Instruct measured |
| DTBench | 59.5% | 80.5% | Qwen3.5 Plus 2026-04-20 |
| LMCA | 17.5% | 36.4% | Qwen3.5 Plus 2026-04-20 |
| Fiction.LiveBench | 33.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| CL-bench | Not measured | 19.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench Life | Not measured | 12.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text | 1274 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: instruction following | 1242 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: creative writing | 1250 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: English | 1303 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: non-English | 1236 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Chinese | 1217 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: German | 1251 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Japanese | 1150 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Korean | 1142 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: French | 1282 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Spanish | 1269 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Russian | 1252 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Polish | 1259 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: multi-turn | 1280 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: longer queries | 1255 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: writing and language | 1255 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: entertainment and media | 1241 | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 | 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 3.3 70B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3.5 Plus 2026-04-20 costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 Plus 2026-04-20 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 3.3 70B Instruct | Qwen3.5 Plus 2026-04-20 |
|---|---|---|
| Maker | Meta Llama | Qwen |
| Weights | Open weights | No public weights listed |
| Released | December 6, 2024 | April 27, 2026 |
| Context window | 131K | 1M |
| Input $/Mtok | $0.45 | $0.30 |
| Output $/Mtok | $0.72 | $1.80 |
| Coding index | Not benchmarked | 39.5 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $1.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.3 70B Instruct better than Qwen3.5 Plus 2026-04-20 for coding?
Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.3 70B Instruct for output tokens 2.5x cheaper ($0.72 vs $1.80 per million).
Which is cheaper, Llama 3.3 70B Instruct or Qwen3.5 Plus 2026-04-20?
Llama 3.3 70B Instruct costs $0.45 per million input tokens and $0.72 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Cost per solved task is known for Qwen3.5 Plus 2026-04-20 only.
Which has the bigger context window, Llama 3.3 70B Instruct or Qwen3.5 Plus 2026-04-20?
Qwen3.5 Plus 2026-04-20, with 1M tokens against 131K.
How many benchmarks is the Llama 3.3 70B Instruct vs Qwen3.5 Plus 2026-04-20 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Llama 3.3 70B Instruct's coding index rests on 0 independent benchmarks and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.