Model comparison
Gemma 4 31B IT vs Llama 3.2 1B
Gemma 4 31B IT is the stronger model overall, scoring 43.2 to 19.9 on the Noometry Index. Llama 3.2 1B costs 2.2× less per token, which makes it the better buy when Gemma 4 31B IT's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
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MetaSummary
- They share 17 benchmarks with published results for both. Gemma 4 31B IT scores higher in 8 categories and Llama 3.2 1B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemma 4 31B IT leads 60.7 to 21.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.3% for Gemma 4 31B IT and 0.6% for Llama 3.2 1B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.09 / $0.34 for Gemma 4 31B IT.
- Gemma 4 31B IT accepts more context: 262K tokens versus 60K.
Side by side
| Gemma 4 31B IT | Llama 3.2 1B | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 43.2 | 19.9 |
| Released | 2026-04-02 | 2024-09-24 |
| Weights | Open | Open |
| Context window | 262K | 60K |
| Max output | 33K | 54K |
| Input $ / M tokens | $0.09 | $0.027 |
| Output $ / M tokens | $0.34 | $0.20 |
| Results tracked | 35 | 22 |
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Category by category
Coding Gemma 4 31B IT leads
Gemma 4 31B IT: 41.9 (#98), Llama 3.2 1B: 20.6 (#333)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1459 | 1071 |
| LMArena WebDev | 1364 | — |
| SciCode | 43.4% | — |
| WeirdML | 52.3% | — |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
| ALE-Bench | 925.5 | — |
Agentic & Tool Use Not comparable
Gemma 4 31B IT: —, Llama 3.2 1B: 14.5 (#142)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10.8% |
| BALROG | — | 6.6% |
Reasoning Gemma 4 31B IT leads
Gemma 4 31B IT: 26.4 (#119), Llama 3.2 1B: 15.6 (#304)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 5% | 0% |
| LMArena Hard Prompts | 1448 | 1044 |
| Epoch Capabilities Index | 142.74 | 101.95 |
| Kagi LLM Benchmark | 63.5% | — |
| NYT Connections (extended) | 70.6% | — |
| CritPt | 1.4% | — |
| Thematic Generalization | 53% | — |
| DTBench | 82.7% | — |
| LMCA | 39.3% | — |
| Surface Evolver Bench | 30.6% | — |
Math Gemma 4 31B IT leads
Gemma 4 31B IT: 41.3 (#72), Llama 3.2 1B: 9.7 (#308)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.3% | 0.6% |
| LMArena Math | 1464 | 1086 |
Knowledge Gemma 4 31B IT leads
Gemma 4 31B IT: 37.9 (#141), Llama 3.2 1B: 7.2 (#307)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 75.8% | 23.9% |
| LMArena Expert | 1465 | 1007 |
| SimpleQA Verified | 10.4% | — |
| Vectara Hallucination Rate | 7.4% | — |
Multimodal Not comparable
Gemma 4 31B IT: 41.0 (#32), Llama 3.2 1B: —
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1278 | — |
| LMArena Document | 1425 | — |
Multilingual Gemma 4 31B IT leads
Gemma 4 31B IT: 54.0 (#52), Llama 3.2 1B: 23.9 (#287)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1431 | 973 |
| LMArena Chinese | 1478 | 958 |
| LMArena Russian | 1462 | 941 |
| LMArena French | 1436 | — |
| LMArena German | — | 1014 |
| LMArena Spanish | 1443 | — |
Instruction Following Gemma 4 31B IT leads
Gemma 4 31B IT: 75.6 (#58), Llama 3.2 1B: 52.6 (#285)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1433 | 1031 |
Long Context Gemma 4 31B IT leads
Gemma 4 31B IT: 44.2 (#67), Llama 3.2 1B: 31.9 (#269)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1446 | 1050 |
Writing & Preference Gemma 4 31B IT leads
Gemma 4 31B IT: 60.7 (#92), Llama 3.2 1B: 21.4 (#305)
| Benchmark | Gemma 4 31B IT | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1443 | 1055 |
| LMArena Creative Writing | 1416 | 1033 |
| EQ-Bench Creative Writing | 1368 | 200 |
| LMArena Multi-Turn | 1452 | 1030 |
| EQ-Bench 4 | 1120 | — |
Frequently asked questions
Is Gemma 4 31B IT better than Llama 3.2 1B?
Gemma 4 31B IT is the stronger model overall, scoring 43.2 to 19.9 on the Noometry Index. Llama 3.2 1B costs 2.2× less per token, which makes it the better buy when Gemma 4 31B IT's lead doesn't matter for your workload.
Which is cheaper, Gemma 4 31B IT or Llama 3.2 1B?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Gemma 4 31B IT lists at $0.09 and $0.34.
Is Gemma 4 31B IT or Llama 3.2 1B better for coding?
Gemma 4 31B IT scores higher on coding benchmarks: 41.9 versus 20.6 in the Noometry coding category.
Which has the bigger context window?
Gemma 4 31B IT does, with 262K tokens against 60K.
How many benchmarks do Gemma 4 31B IT and Llama 3.2 1B share?
17 benchmarks have published results for both models. Gemma 4 31B IT has 35 scored results on Noometry and Llama 3.2 1B has 22.