Compare / Llama 3.3 70B Instruct vs GPT-4.1 Nano
Llama 3.3 70B Instruct vs GPT-4.1 Nano
Which is cheaper, which is more capable, and which does better at each kind of work, from 23 results on 3 sources that measured both models.
Llama 3.3 70B Instruct or GPT-4.1 Nano? The short answer
- GPT-4.1 Nano is cheaper: $0.18 against $0.64 per million tokens, 3.7 times less.
- They score about the same on the Artificial Analysis Intelligence Index (7.7 and 7.8).
- On our business benchmarks, Llama 3.3 70B Instruct ranks higher for agents and tool use.
- On our business benchmarks, GPT-4.1 Nano ranks higher for reasoning and knowledge and writing.
At a glance
| Llama 3.3 70B Instruct | GPT-4.1 Nano | |
|---|---|---|
| Price per million tokens | $0.59 in · $0.79 out | $0.10 in · $0.40 out |
| Blended (3 in : 1 out) | $0.64 | $0.18 |
| Cheapest host, blended | $0.16 (DeepInfra, FP8) | $0.18 (Azure) |
| Intelligence Index | 7.7 | 7.8 |
| Spring Prompt overall | – | – |
| Output speed, tokens a second | 80 | – |
| Context window | 131,072 tokens | 1,047,576 tokens |
| Weights | Open | Closed |
| Developer based in | the US | the US |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among models available today, for each kind of work, from our own benchmarks and licensed sources. The better rank is in green.
| Use case | Llama 3.3 70B Instruct | GPT-4.1 Nano |
|---|---|---|
| Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls | 127 of 161 | 139 of 161 |
| Reasoning and knowledgeHard questions across science, maths and general knowledge | 174 of 195 | 169 of 195 |
| WritingWhat people prefer in blind comparisons, and judged writing quality | 165 of 187 | 162 of 187 |
| Sticking to the factsSummarising without inventing things, and factual answers | not measured | 151 of 153 |
Every shared result
| Benchmark | Metric | Llama 3.3 70B Instruct | GPT-4.1 Nano |
|---|---|---|---|
| Arena (formerly LMArena)reported | Business, management and financeArena rating | 1,304 | 1,321 |
| Arena (formerly LMArena)reported | Creative writingArena rating | 1,285 | 1,307 |
| Arena (formerly LMArena)reported | Expert promptsArena rating | 1,298 | 1,313 |
| Arena (formerly LMArena)reported | Instruction followingArena rating | 1,293 | 1,300 |
| Arena (formerly LMArena)reported | OverallArena rating | 1,318 | 1,322 |
| Arena (formerly LMArena)reported | Writing, literature and languageArena rating | 1,292 | 1,299 |
| Artificial Analysisreported | Artificial Analysis Coding Indexindex score | 11.9 | 11.1 |
| Artificial Analysisreported | Artificial Analysis Intelligence Indexindex score | 7.70 | 7.80 |
| Artificial Analysisreported | GPQA Diamond% of questions | 49.8% | 51.2% |
| Artificial Analysisreported | Humanity's Last Exam% of questions | 3.6% | 3.8% |
| Artificial Analysisreported | IFBench% of instructions | 47.1% | 32.0% |
| Artificial Analysisreported | Long-context reasoning (AA-LCR)% of questions | 15.7% | 20.3% |
| Artificial Analysisreported | Terminal-Bench 2.1% of tasks | 4.9% | 3.7% |
| Artificial Analysisreported | Terminal-Bench Hard% of tasks | 3.0% | 3.8% |
| Artificial Analysisreported | Τ²-bench telecom% of tasks | 26.6% | 17.3% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Irrelevance detection% correct | 53.5% | 83.4% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Memory% correct | 8.2% | 18.9% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Multi-turn tasks% correct | 21.5% | 23.6% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Overall accuracy% correct | 31.9% | 33.0% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Relevance detection% correct | 100.0% | 93.8% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Single-turn calls (curated)% correct | 88.0% | 73.0% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Single-turn calls (user-contributed)% correct | 76.6% | 60.8% |
| Berkeley Function Calling Leaderboard (BFCL) V4reported | Web search% correct | 10.0% | 11.0% |
Bold green marks the better value on that metric. Where a source reports ranges that overlap, the difference may not be meaningful; see the benchmark page for ranges.
Quick answers
Is Llama 3.3 70B Instruct better than GPT-4.1 Nano?
It depends on the task. Among models available today, on our benchmarks and licensed sources, Llama 3.3 70B Instruct ranks higher for agents and tool use; GPT-4.1 Nano ranks higher for reasoning and knowledge and writing.
Which is cheaper, Llama 3.3 70B Instruct or GPT-4.1 Nano?
GPT-4.1 Nano costs $0.18 per million tokens (three input to one output), against $0.64 for Llama 3.3 70B Instruct.
Run Llama 3.3 70B Instruct and GPT-4.1 Nano on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.