# Claude Sonnet 5 vs Llama-3.3-70B-Instruct

> Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 26× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-sonnet-5-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. Claude Sonnet 5 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 Claude Sonnet 5 leads 66.1 to 14.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.7% for Claude Sonnet 5 and 5.1% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 128K.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 54.5 | 30.3 |
| Rank | 26 | 283 |
| Context | 1M | 128K |
| Input $/M | $2 | $0.10 |
| Output $/M | $10 | $0.32 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 5: 55.5 (#20)
- Llama-3.3-70B-Instruct: 30.6 (#284)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| SciCode | 53.6% | 26% |
| WeirdML | 68.8% | 14.4% |
| LMArena Coding | 1483 | 1268 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| LMArena WebDev | 1540 | — |
| GSO | 37.3% | — |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
| ALE-Bench | 1,463 | — |

## Agentic & Tool Use

- Claude Sonnet 5: 42.7 (#16)
- Llama-3.3-70B-Instruct: 25.6 (#100)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| APEX-Agents | 54.5% | — |
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |

## Reasoning

- Claude Sonnet 5: 48.2 (#37)
- Llama-3.3-70B-Instruct: 13.7 (#325)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 60.6% | 19.9% |
| CritPt | 16.9% | 0% |
| LMArena Hard Prompts | 1461 | 1257 |
| DTBench | 92.5% | 59.5% |
| LMCA | 50% | 17.5% |
| Epoch Capabilities Index | 156.34 | 127.32 |
| ForecastBench | 61.1 | 58.6 |
| NYT Connections (extended) | 75.1% | — |
| Chess Puzzles | 35% | — |
| LiveBench Reasoning | — | 50.8% |
| Mystery Game Puzzles | 35% | — |
| LiveBench Data Analysis | — | 49.5% |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| LiveBench | — | 50.2% |

## Math

- Claude Sonnet 5: 66.1 (#21)
- Llama-3.3-70B-Instruct: 14.3 (#292)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.7% | 5.1% |
| LMArena Math | 1467 | 1268 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 77% | — |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |

## Knowledge

- Claude Sonnet 5: 55.7 (#42)
- Llama-3.3-70B-Instruct: 30.5 (#220)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 90.5% | 47.4% |
| LMArena Expert | 1491 | 1225 |
| SimpleQA Verified | 33.7% | — |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| MMLU | — | 86.3% |

## Multimodal

- Claude Sonnet 5: 42.4 (#26)
- Llama-3.3-70B-Instruct: —

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1275 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |

## Multilingual

- Claude Sonnet 5: 54.0 (#55)
- Llama-3.3-70B-Instruct: 40.1 (#215)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1431 | 1236 |
| LMArena Chinese | 1475 | 1217 |
| LMArena French | 1457 | 1280 |
| LMArena German | 1448 | 1251 |
| LMArena Japanese | 1422 | 1149 |
| LMArena Korean | 1411 | 1142 |
| LMArena Russian | 1452 | 1252 |
| LMArena Spanish | 1436 | 1269 |

## Instruction Following

- Claude Sonnet 5: 76.6 (#39)
- Llama-3.3-70B-Instruct: 71.3 (#152)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1453 | 1242 |
| LiveBench Instruction Following | — | 82.7% |

## Long Context

- Claude Sonnet 5: 44.8 (#53)
- Llama-3.3-70B-Instruct: 26.4 (#290)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1464 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- Claude Sonnet 5: 69.4 (#24)
- Llama-3.3-70B-Instruct: 47.8 (#203)

| Benchmark | Claude Sonnet 5 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1443 | 1274 |
| LMArena Creative Writing | 1416 | 1250 |
| LMArena Multi-Turn | 1454 | 1279 |
| EQ-Bench Creative Writing | 1794 | — |
| EQ-Bench 4 | 1236 | — |
| LiveBench Language | — | 39.2% |

## FAQ

### Is Claude Sonnet 5 better than Llama-3.3-70B-Instruct?

Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 30.3 on the Noometry Index. Llama-3.3-70B-Instruct costs 26× 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-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Claude Sonnet 5 lists at $2 and $10.

### Is Claude Sonnet 5 or Llama-3.3-70B-Instruct better for coding?

Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 30.6 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-3.3-70B-Instruct share?

27 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and Llama-3.3-70B-Instruct has 43.