Model comparison
Claude Sonnet 5 vs Llama 3.1-70B
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 10× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
MetaSummary
- They share 24 benchmarks with published results for both. Claude Sonnet 5 scores higher in 9 categories and Llama 3.1-70B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 5 leads 66.1 to 12.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.7% for Claude Sonnet 5 and 3.6% for Llama 3.1-70B.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5 | Llama 3.1-70B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 54.5 | 29.4 |
| Released | 2026-06-29 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 1M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $2 | $0.40 |
| Output $ / M tokens | $10 | $0.40 |
| Results tracked | 51 | 35 |
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Category by category
Coding Claude Sonnet 5 leads
Claude Sonnet 5: 55.5 (#20), Llama 3.1-70B: 29.8 (#292)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| WeirdML | 68.8% | 9% |
| LMArena Coding | 1483 | 1260 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| LMArena WebDev | 1540 | — |
| SciCode | 53.6% | — |
| GSO | 37.3% | — |
| BigCodeBench Instruct | — | 46.1% |
| BigCodeBench Complete | — | 54.8% |
| ALE-Bench | 1,463 | — |
Agentic & Tool Use Claude Sonnet 5 leads
Claude Sonnet 5: 42.7 (#16), Llama 3.1-70B: 24.9 (#104)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| APEX-Agents | 54.5% | — |
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |
Reasoning Claude Sonnet 5 leads
Claude Sonnet 5: 48.2 (#37), Llama 3.1-70B: 20.8 (#215)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Hard Prompts | 1461 | 1241 |
| DTBench | 92.5% | 60% |
| LMCA | 50% | 14.8% |
| Epoch Capabilities Index | 156.34 | 125.91 |
| SimpleBench | 60.6% | — |
| NYT Connections (extended) | 75.1% | — |
| CritPt | 16.9% | — |
| Chess Puzzles | 35% | — |
| Mystery Game Puzzles | 35% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 61.1 | — |
Math Claude Sonnet 5 leads
Claude Sonnet 5: 66.1 (#21), Llama 3.1-70B: 12.7 (#298)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.7% | 3.6% |
| LMArena Math | 1467 | 1252 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 77% | — |
| Omni-MATH | — | 21% |
| MATH Level 5 | — | 36.7% |
Knowledge Claude Sonnet 5 leads
Claude Sonnet 5: 55.7 (#42), Llama 3.1-70B: 24.1 (#264)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | 90.5% | 44.2% |
| LMArena Expert | 1491 | 1209 |
| SimpleQA Verified | 33.7% | — |
| MMLU-Pro | — | 65.3% |
| GPQA (HELM) | — | 42.6% |
| MMLU | — | 80.1% |
Multimodal Not comparable
Claude Sonnet 5: 42.4 (#26), Llama 3.1-70B: —
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Vision | 1275 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |
Multilingual Claude Sonnet 5 leads
Claude Sonnet 5: 54.0 (#55), Llama 3.1-70B: 38.9 (#220)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | 1431 | 1219 |
| LMArena Chinese | 1475 | 1215 |
| LMArena French | 1457 | 1260 |
| LMArena German | 1448 | 1222 |
| LMArena Japanese | 1422 | 1132 |
| LMArena Korean | 1411 | 1140 |
| LMArena Russian | 1452 | 1234 |
| LMArena Spanish | 1436 | 1253 |
Instruction Following Claude Sonnet 5 leads
Claude Sonnet 5: 76.6 (#39), Llama 3.1-70B: 65.5 (#218)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Instruction Following | 1453 | 1231 |
| IFEval | — | 82.1% |
Long Context Claude Sonnet 5 leads
Claude Sonnet 5: 44.8 (#53), Llama 3.1-70B: 37.6 (#208)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | 1464 | 1241 |
Writing & Preference Claude Sonnet 5 leads
Claude Sonnet 5: 69.4 (#24), Llama 3.1-70B: 35.6 (#262)
| Benchmark | Claude Sonnet 5 | Llama 3.1-70B |
|---|---|---|
| LMArena Text | 1443 | 1261 |
| LMArena Creative Writing | 1416 | 1232 |
| EQ-Bench Creative Writing | 1794 | 784 |
| LMArena Multi-Turn | 1454 | 1256 |
| WildBench | — | 75.8% |
| EQ-Bench 4 | 1236 | — |
Frequently asked questions
Is Claude Sonnet 5 better than Llama 3.1-70B?
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 10× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5 or Llama 3.1-70B?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Claude Sonnet 5 lists at $2 and $10.
Is Claude Sonnet 5 or Llama 3.1-70B better for coding?
Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 29.8 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 5 does, with 1M tokens against 128K.
How many benchmarks do Claude Sonnet 5 and Llama 3.1-70B share?
24 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and Llama 3.1-70B has 35.