Model comparison
Llama 3.2 1B vs Qwen3.5 35B-A3B
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 20.1 on the Noometry Index. Llama 3.2 1B costs 9.8× less per token, which makes it the better buy when Qwen3.5 35B-A3B's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen3.5 35B-A3B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5 35B-A3B leads 47.8 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Llama 3.2 1B and 70% for Qwen3.5 35B-A3B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.25 / $2 for Qwen3.5 35B-A3B.
- Qwen3.5 35B-A3B accepts more context: 262K tokens versus 60K.
Side by side
| Llama 3.2 1B | Qwen3.5 35B-A3B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 42.0 |
| Released | 2024-09-24 | 2026-02-01 |
| Weights | Open | Open |
| Context window | 60K | 262K |
| Max output | 54K | 66K |
| Input $ / M tokens | $0.027 | $0.25 |
| Output $ / M tokens | $0.20 | $2 |
| Results tracked | 22 | 28 |
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Category by category
Coding Qwen3.5 35B-A3B leads
Llama 3.2 1B: 21.1 (#338), Qwen3.5 35B-A3B: 33.8 (#251)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Coding | 1070 | 1410 |
| LMArena WebDev | — | 1254 |
| SciCode | — | 29.3% |
| BigCodeBench Instruct | 8.2% | — |
| BigCodeBench Complete | 11.3% | — |
Agentic & Tool Use Not comparable
Llama 3.2 1B: 14.6 (#150), Qwen3.5 35B-A3B: —
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |
Reasoning Qwen3.5 35B-A3B leads
Llama 3.2 1B: 16.2 (#308), Qwen3.5 35B-A3B: 24.6 (#161)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 10% |
| LMArena Hard Prompts | 1044 | 1400 |
| Epoch Capabilities Index | 101.99 | 142.52 |
| CritPt | — | 0.6% |
| DTBench | — | 80% |
| LMCA | — | 29.5% |
Math Qwen3.5 35B-A3B leads
Llama 3.2 1B: 10.4 (#313), Qwen3.5 35B-A3B: 39.9 (#97)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 70% |
| LMArena Math | 1086 | 1404 |
| MathArena Final-Answer Competitions | — | 56% |
Knowledge Qwen3.5 35B-A3B leads
Llama 3.2 1B: 7.2 (#312), Qwen3.5 35B-A3B: 47.8 (#79)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| GPQA Diamond | 23.9% | 83.5% |
| LMArena Expert | 1007 | 1408 |
| Vectara Hallucination Rate | — | 10.5% |
Multilingual Qwen3.5 35B-A3B leads
Llama 3.2 1B: 23.8 (#292), Qwen3.5 35B-A3B: 50.0 (#127)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Non-English | 973 | 1378 |
| LMArena Chinese | 959 | 1457 |
| LMArena German | 1014 | 1367 |
| LMArena Russian | 941 | 1376 |
| LMArena French | — | 1412 |
| LMArena Japanese | — | 1325 |
| LMArena Korean | — | 1356 |
| LMArena Spanish | — | 1392 |
Instruction Following Qwen3.5 35B-A3B leads
Llama 3.2 1B: 52.4 (#290), Qwen3.5 35B-A3B: 72.8 (#128)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Instruction Following | 1031 | 1379 |
Long Context Qwen3.5 35B-A3B leads
Llama 3.2 1B: 31.9 (#274), Qwen3.5 35B-A3B: 42.4 (#127)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Longer Query | 1050 | 1389 |
Writing & Preference Qwen3.5 35B-A3B leads
Llama 3.2 1B: 21.3 (#310), Qwen3.5 35B-A3B: 57.9 (#124)
| Benchmark | Llama 3.2 1B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Text | 1055 | 1395 |
| LMArena Creative Writing | 1033 | 1346 |
| LMArena Multi-Turn | 1030 | 1390 |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen3.5 35B-A3B?
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 20.1 on the Noometry Index. Llama 3.2 1B costs 9.8× less per token, which makes it the better buy when Qwen3.5 35B-A3B's lead doesn't matter for your workload.
Which is cheaper, Llama 3.2 1B or Qwen3.5 35B-A3B?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen3.5 35B-A3B lists at $0.25 and $2.
Is Llama 3.2 1B or Qwen3.5 35B-A3B better for coding?
Qwen3.5 35B-A3B scores higher on coding benchmarks: 33.8 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5 35B-A3B does, with 262K tokens against 60K.
How many benchmarks do Llama 3.2 1B and Qwen3.5 35B-A3B share?
17 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3.5 35B-A3B has 28.