Model comparison
Gemini 4 Argon vs Llama-3.3-70B-Instruct
Gemini 4 Argon is the stronger model overall, scoring 56.5 to 30.6 on the Noometry Index.
Last verified . 15 shared benchmarks.
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MetaSummary
- They share 15 benchmarks with published results for both. Gemini 4 Argon scores higher in 9 categories and Llama-3.3-70B-Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 4 Argon leads 73.9 to 15.3.
- The biggest single-benchmark swing is SciCode: 61.8% for Gemini 4 Argon and 26% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.
Side by side
| Gemini 4 Argon | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 56.5 | 30.6 |
| Released | 2026-09-30 | 2024-12-06 |
| Weights | Proprietary | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.32 |
| Results tracked | 21 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 4 Argon leads
Gemini 4 Argon: 62.0 (#9), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| SciCode | 61.8% | 26% |
| LMArena Coding | 1550 | 1268 |
| LMArena WebDev | 1678 | — |
| FrontierSWE | 55% | — |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
Agentic & Tool Use Gemini 4 Argon leads
Gemini 4 Argon: 49.2 (#8), Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| APEX-Agents | 82.2% | — |
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
| Vending-Bench 2 | 13,718 | — |
Reasoning Gemini 4 Argon leads
Gemini 4 Argon: 44.2 (#47), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| CritPt | 27.1% | 0% |
| LMArena Hard Prompts | 1548 | 1257 |
| SimpleBench | — | 19.9% |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| Epoch Capabilities Index | — | 127.33 |
| ForecastBench | — | 58.6 |
| LiveBench | — | 50.2% |
Math Gemini 4 Argon leads
Gemini 4 Argon: 73.9 (#17), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1536 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| ProofBench | 99% | — |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
Knowledge Gemini 4 Argon leads
Gemini 4 Argon: 43.9 (#89), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1553 | 1225 |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| MMLU | — | 86.3% |
Multimodal Not comparable
Gemini 4 Argon: 46.5 (#14), Llama-3.3-70B-Instruct: —
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| Blueprint-Bench 2 | 54.4% | — |
Multilingual Gemini 4 Argon leads
Gemini 4 Argon: 60.3 (#1), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1523 | 1236 |
| LMArena Chinese | 1610 | 1217 |
| LMArena Russian | 1537 | 1252 |
| LMArena Spanish | 1497 | 1270 |
| LMArena French | — | 1281 |
| LMArena German | — | 1251 |
| LMArena Japanese | — | 1150 |
| LMArena Korean | — | 1143 |
Instruction Following Gemini 4 Argon leads
Gemini 4 Argon: 80.1 (#2), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1538 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
Long Context Gemini 4 Argon leads
Gemini 4 Argon: 47.6 (#15), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1549 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Gemini 4 Argon leads
Gemini 4 Argon: 71.4 (#19), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Gemini 4 Argon | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1534 | 1274 |
| LMArena Creative Writing | 1531 | 1250 |
| LMArena Multi-Turn | 1557 | 1280 |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Gemini 4 Argon better than Llama-3.3-70B-Instruct?
Gemini 4 Argon is the stronger model overall, scoring 56.5 to 30.6 on the Noometry Index.
Is Gemini 4 Argon or Llama-3.3-70B-Instruct better for coding?
Gemini 4 Argon scores higher on coding benchmarks: 62.0 versus 31.0 in the Noometry coding category.
How many benchmarks do Gemini 4 Argon and Llama-3.3-70B-Instruct share?
15 benchmarks have published results for both models. Gemini 4 Argon has 21 scored results on Noometry and Llama-3.3-70B-Instruct has 43.