GPT-5 nano vs Llama 3.3 70B Instruct
GPT-5 nano vs Llama 3.3 70B Instruct: GPT-5 nano is cheaper by 93% on average. GPT-5 nano from Azure OpenAI (272,000-token context, reasoning, tool calls) vs. Llama 3.3 70B Instruct from Azure AI Foundry (128,000-token context, tool calls). Use Agent Command Center to A/B both in shadow mode and pick the winner per workload.
Side-by-side cost
Live workload comparison
Same workload run through both models. The cheaper one is highlighted.
3,000
0272,000
400
0128,000
5,000
01,000,000
At this workload, GPT-5 nano is 87% cheaper than Llama 3.3 70B Instruct — a savings of $320/month ($3,842/year).
Production recipe — Agent Command Center
strategy: cost-optimized
primary:
model: gpt-5-nano
provider: azure-openai
fallback:
model: llama-3-3-70b-instruct
provider: azure-ai-foundry
shadow: { sample_rate: 0.05 } # mirror 5% of traffic to compare quality live| GPT-5 nano | Llama 3.3 70B Instruct | |
|---|---|---|
| Input price | $0.0500/M | $0.710/M |
| Output price | $0.400/M | $0.710/M |
| Context window | 272,000 | 128,000 |
| Max output | 128,000 | 2,048 |
| Function calling | ✓ | ✓ |
| Vision | ✓ | — |
| Audio input | — | — |
| Reasoning | ✓ | — |
| Prompt caching | ✓ | — |
| Structured output | ✓ | — |
| Pricing verified | May 12, 2026 | May 12, 2026 |
Benchmark comparison
Side-by-side public benchmark scores. Greener bar = winner.
Chatbot Arena ELOgeneral
GPT-5 nano
1,325
Llama 3.3 70B Instruct
1,268
HumanEvalcode
GPT-5 nano
86.3%
Llama 3.3 70B Instruct
88.4%
MMLU-Proreasoning⚠ different settings
GPT-5 nano
73.0%
Llama 3.3 70B Instruct
68.9%