# Llama-3.3-70B-Instruct vs Phi-4

> Llama-3.3-70B-Instruct and Phi-4 score almost the same on the Noometry Index (30.3 vs 30.9), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/llama-3-3-70b-instruct-vs-phi-4
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 4 categories and Phi-4 in 5 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where Llama-3.3-70B-Instruct leads 71.3 to 60.6.
- The biggest single-benchmark swing is LiveBench Instruction Following: 82.7% for Llama-3.3-70B-Instruct and 58.4% for Phi-4.
- Phi-4 is cheaper at $0.07 / $0.14 per million input/output tokens, against $0.10 / $0.32 for Llama-3.3-70B-Instruct.

## Snapshot

| | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 30.3 | 30.9 |
| Rank | 283 | 269 |
| Context | 128K | 128K |
| Input $/M | $0.10 | $0.07 |
| Output $/M | $0.32 | $0.14 |
| Weights | Open | Open |

## Coding

- Llama-3.3-70B-Instruct: 30.6 (#284)
- Phi-4: 33.8 (#237)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| BigCodeBench Instruct | 46.9% | 45.5% |
| LiveBench Coding | 36.6% | 30.7% |
| LMArena Coding | 1268 | 1231 |
| BigCodeBench Complete | 57.5% | 55.4% |
| SciCode | 26% | — |
| WeirdML | 14.4% | — |

## Agentic & Tool Use

- Llama-3.3-70B-Instruct: 25.6 (#100)
- Phi-4: 22.6 (#120)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | 28.8% |
| BALROG | 23% | 11.6% |

## Reasoning

- Llama-3.3-70B-Instruct: 13.7 (#325)
- Phi-4: 17.0 (#287)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| LiveBench Reasoning | 50.8% | 47.8% |
| LMArena Hard Prompts | 1257 | 1220 |
| LiveBench Data Analysis | 49.5% | 45.2% |
| Epoch Capabilities Index | 127.32 | 130.43 |
| LiveBench | 50.2% | 41.6% |
| SimpleBench | 19.9% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 1% |
| DTBench | 59.5% | — |
| LMCA | 17.5% | — |
| ForecastBench | 58.6 | — |

## Math

- Llama-3.3-70B-Instruct: 14.3 (#292)
- Phi-4: 19.6 (#279)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 13.8% |
| LiveBench Math | 42.2% | 42% |
| LMArena Math | 1268 | 1246 |
| MATH Level 5 | 41.6% | 64.9% |

## Knowledge

- Llama-3.3-70B-Instruct: 30.5 (#220)
- Phi-4: 32.5 (#204)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| GPQA Diamond | 47.4% | 56.1% |
| Confabulations | 22.8% | 29.4% |
| Vectara Hallucination Rate | 4.1% | 3.7% |
| LMArena Expert | 1225 | 1203 |
| MMLU | 86.3% | 84.8% |

## Multilingual

- Llama-3.3-70B-Instruct: 40.1 (#215)
- Phi-4: 37.4 (#232)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| LMArena Non-English | 1236 | 1197 |
| LMArena Chinese | 1217 | 1211 |
| LMArena French | 1280 | 1223 |
| LMArena German | 1251 | 1222 |
| LMArena Japanese | 1149 | 1158 |
| LMArena Korean | 1142 | 1151 |
| LMArena Russian | 1252 | 1209 |
| LMArena Spanish | 1269 | 1234 |

## Instruction Following

- Llama-3.3-70B-Instruct: 71.3 (#152)
- Phi-4: 60.6 (#246)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| LiveBench Instruction Following | 82.7% | 58.4% |
| LMArena Instruction Following | 1242 | 1201 |

## Long Context

- Llama-3.3-70B-Instruct: 26.4 (#290)
- Phi-4: 36.9 (#221)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| LMArena Longer Query | 1256 | 1217 |
| Fiction.LiveBench | 33.3% | — |

## Writing & Preference

- Llama-3.3-70B-Instruct: 47.8 (#203)
- Phi-4: 40.7 (#239)

| Benchmark | Llama-3.3-70B-Instruct | Phi-4 |
|---|---|---|
| LMArena Text | 1274 | 1217 |
| LMArena Creative Writing | 1250 | 1182 |
| LMArena Multi-Turn | 1279 | 1206 |
| LiveBench Language | 39.2% | 25.6% |
| Short-Story Creative Writing | — | 62.6% |

## FAQ

### Is Llama-3.3-70B-Instruct better than Phi-4?

Llama-3.3-70B-Instruct and Phi-4 score almost the same on the Noometry Index (30.3 vs 30.9), so choose on price, context window or the category you care about most.

### Which is cheaper, Llama-3.3-70B-Instruct or Phi-4?

Phi-4 is cheaper. It lists at $0.07 per million input tokens and $0.14 per million output tokens; Llama-3.3-70B-Instruct lists at $0.10 and $0.32.

### Is Llama-3.3-70B-Instruct or Phi-4 better for coding?

Phi-4 scores higher on coding benchmarks: 33.8 versus 30.6 in the Noometry coding category.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do Llama-3.3-70B-Instruct and Phi-4 share?

35 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Phi-4 has 37.