GPT-5 vs Llama 3.3 70B: Detailed Comparison
Choosing between GPT-5 (OpenAI) and
Llama 3.3 70B (Meta) comes down to three things:
per-token pricing, context window, and which capability matters most for your workload.
GPT-5 costs $1.25/M input vs
$0.59/M for Llama 3.3 70B;
context windows are 400K vs
128K tokens. Detailed breakdown below.
Side-by-side specs
| Spec | GPT-5 | Llama 3.3 70B |
|---|
| Provider | OpenAI | Meta |
|---|
| Released | 2025-08-07 | 2024-12-06 |
|---|
| Input price |
$1.25/M |
$0.59/M |
| Output price |
$10.00/M |
$0.79/M |
| Cached input |
$0.1300/M |
— |
| Context window |
400K |
128K |
| Max output |
128K |
8K |
| Modalities |
text image |
text |
| Tokenizer |
o200k_base |
llama-3 |
Capability matrix
| Capability | GPT-5 | Llama 3.3 70B |
|---|
| function calling |
Yes |
Yes |
| json mode |
Yes |
Yes |
| vision |
Yes |
No |
| streaming |
Yes |
Yes |
| reasoning |
Yes |
No |
| tool use |
No |
Yes |
Benchmark comparison
Higher is better for all benchmarks shown.
Per-call cost on typical workloads
| Workload (in/out tokens) | GPT-5 | Llama 3.3 70B | Cheaper by |
|---|
| Standard chat (1K / 500) |
$0.006250 |
$0.000985 |
Llama 3.3 70B by $0.005265 |
| RAG (4K / 500) |
$0.010000 |
$0.002755 |
Llama 3.3 70B by $0.007245 |
| Long doc (20K / 1K) |
$0.035000 |
$0.012590 |
Llama 3.3 70B by $0.022410 |
| Very long context (100K / 2K) |
$0.140000 |
$0.060185 |
Llama 3.3 70B by $0.079815 |
When to choose GPT-5 over Llama 3.3 70B
- Larger context window (400K vs 128K) — relevant when whole documents or long histories must fit in a single call.
- Supports vision — Llama 3.3 70B does not.
- Supports reasoning — Llama 3.3 70B does not.
When to choose Llama 3.3 70B over GPT-5
- Per-token input cost is 53% lower than GPT-5.
- Supports tool use — GPT-5 does not.
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