Model comparison
Llama-3.3-70B-Instruct vs Phi-4 Mini
Llama-3.3-70B-Instruct and Phi-4 Mini score almost the same on the Noometry Index (30.6 vs 30.9), so choose on price, context window or the category you care about most.
Last verified . 3 shared benchmarks.
Meta
MicrosoftSummary
- They share 3 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 2 categories and Phi-4 Mini in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Phi-4 Mini leads 22.4 to 14.1.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 4.1% for Llama-3.3-70B-Instruct and 23.5% for Phi-4 Mini.
- Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.10 / $0.32 for Llama-3.3-70B-Instruct.
Side by side
| Llama-3.3-70B-Instruct | Phi-4 Mini | |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 30.6 | 30.9 |
| Released | 2024-12-06 | 2024-12-11 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 4K | 4K |
| Input $ / M tokens | $0.10 | $0.075 |
| Output $ / M tokens | $0.32 | $0.30 |
| Results tracked | 43 | 3 |
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Category by category
Coding Llama-3.3-70B-Instruct leads
Llama-3.3-70B-Instruct: 31.0 (#290), Phi-4 Mini: 28.1 (#317)
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| SciCode | 26% | 10.8% |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| LMArena Coding | 1268 | — |
| BigCodeBench Complete | 57.5% | — |
Agentic & Tool Use Not comparable
Llama-3.3-70B-Instruct: 25.8 (#105), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |
Reasoning Phi-4 Mini leads
Llama-3.3-70B-Instruct: 14.1 (#327), Phi-4 Mini: 22.4 (#195)
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| CritPt | 0% | 0% |
| SimpleBench | 19.9% | — |
| LiveBench Reasoning | 50.8% | — |
| LMArena Hard Prompts | 1257 | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| Epoch Capabilities Index | 127.33 | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |
Math Not comparable
Llama-3.3-70B-Instruct: 15.3 (#298), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | — |
| LiveBench Math | 42.2% | — |
| LMArena Math | 1267 | — |
| MATH Level 5 | 41.6% | — |
Knowledge Llama-3.3-70B-Instruct leads
Llama-3.3-70B-Instruct: 30.6 (#226), Phi-4 Mini: 25.3 (#262)
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| Vectara Hallucination Rate | 4.1% | 23.5% |
| GPQA Diamond | 47.4% | — |
| Confabulations | 22.8% | — |
| LMArena Expert | 1225 | — |
| MMLU | 86.3% | — |
Multilingual Not comparable
Llama-3.3-70B-Instruct: 39.9 (#220), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| LMArena Non-English | 1236 | — |
| LMArena Chinese | 1217 | — |
| LMArena French | 1281 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1150 | — |
| LMArena Korean | 1143 | — |
| LMArena Russian | 1252 | — |
| LMArena Spanish | 1270 | — |
Instruction Following Not comparable
Llama-3.3-70B-Instruct: 71.1 (#157), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| LiveBench Instruction Following | 82.7% | — |
| LMArena Instruction Following | 1242 | — |
Long Context Not comparable
Llama-3.3-70B-Instruct: 26.4 (#295), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| Fiction.LiveBench | 33.3% | — |
| LMArena Longer Query | 1256 | — |
Writing & Preference Not comparable
Llama-3.3-70B-Instruct: 47.6 (#207), Phi-4 Mini: —
| Benchmark | Llama-3.3-70B-Instruct | Phi-4 Mini |
|---|---|---|
| LMArena Text | 1274 | — |
| LMArena Creative Writing | 1250 | — |
| LMArena Multi-Turn | 1280 | — |
| LiveBench Language | 39.2% | — |
Frequently asked questions
Is Llama-3.3-70B-Instruct better than Phi-4 Mini?
Llama-3.3-70B-Instruct and Phi-4 Mini score almost the same on the Noometry Index (30.6 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 Mini?
Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 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 Mini better for coding?
Llama-3.3-70B-Instruct scores higher on coding benchmarks: 31.0 versus 28.1 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 Mini share?
3 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Phi-4 Mini has 3.