Llama 3.3 70B vs Qwen3-235B: Detailed Comparison
Choosing between Llama 3.3 70B (Meta) and
Qwen3-235B (Alibaba) comes down to three things:
per-token pricing, context window, and which capability matters most for your workload.
Llama 3.3 70B costs $0.59/M input vs
$0.50/M for Qwen3-235B;
context windows are 128K vs
128K tokens. Detailed breakdown below.
Side-by-side specs
| Spec | Llama 3.3 70B | Qwen3-235B |
|---|
| Provider | Meta | Alibaba |
|---|
| Released | 2024-12-06 | 2025-04-29 |
|---|
| Input price |
$0.59/M |
$0.50/M |
| Output price |
$0.79/M |
$2.00/M |
| Cached input |
— |
— |
| Context window |
128K |
128K |
| Max output |
8K |
8K |
| Modalities |
text |
text |
| Tokenizer |
llama-3 |
qwen |
Capability matrix
| Capability | Llama 3.3 70B | Qwen3-235B |
|---|
| function calling |
Yes |
Yes |
| json mode |
Yes |
Yes |
| streaming |
Yes |
Yes |
| tool use |
Yes |
Yes |
| thinking |
No |
Yes |
Benchmark comparison
Higher is better for all benchmarks shown.
| Benchmark | Category | Llama 3.3 70B | Qwen3-235B | Δ |
|---|
| MMLU |
general |
86.0 |
— |
— |
| HumanEval |
coding |
88.4 |
— |
— |
Per-call cost on typical workloads
| Workload (in/out tokens) | Llama 3.3 70B | Qwen3-235B | Cheaper by |
|---|
| Standard chat (1K / 500) |
$0.000985 |
$0.001500 |
Llama 3.3 70B by $0.000515 |
| RAG (4K / 500) |
$0.002755 |
$0.003000 |
Llama 3.3 70B by $0.000245 |
| Long doc (20K / 1K) |
$0.012590 |
$0.012000 |
Qwen3-235B by $0.000590 |
| Very long context (100K / 2K) |
$0.060185 |
$0.053000 |
Qwen3-235B by $0.007185 |
When to choose Llama 3.3 70B over Qwen3-235B
- Llama 3.3 70B fits when your stack is already on Meta (single billing, SDK, observability surface).
When to choose Qwen3-235B over Llama 3.3 70B
- Per-token input cost is 15% lower than Llama 3.3 70B.
- Supports thinking — Llama 3.3 70B does not.
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