Llama 3.3 70B vs Qwen3-30B-A3B
Llama 3.3 70B (2025) and Qwen3-30B-A3B (2026) are compact production models from AI at Meta and Alibaba. Llama 3.3 70B ships a 8K-token context window, while Qwen3-30B-A3B ships a not-yet-sourced context window. On pricing, Qwen3-30B-A3B costs $0.08/1M input tokens versus $0.9/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3-30B-A3B is ~1025% cheaper at $0.08/1M; pay for Llama 3.3 70B only for vision-heavy evaluation.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-09 | 2026-02-10 |
| Context window | 8K | — |
| Parameters | 70B | 30B |
| Architecture | decoder only | mixture of experts |
| License | True | Apache 2.0 |
| Knowledge cutoff | 2024-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.3 70B | Qwen3-30B-A3B |
|---|---|---|
| Input price | $0.9/1M tokens | $0.08/1M tokens |
| Output price | $0.9/1M tokens | $0.28/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.3 70B | Qwen3-30B-A3B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Llama 3.3 70B, multimodal input: Llama 3.3 70B, function calling: Llama 3.3 70B, tool use: Llama 3.3 70B, and structured outputs: Qwen3-30B-A3B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 3.3 70B lists $0.9/1M input and $0.9/1M output tokens, while Qwen3-30B-A3B lists $0.08/1M input and $0.28/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-30B-A3B lower by about $0.76 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.
Choose Llama 3.3 70B when vision-heavy evaluation are central to the workload. Choose Qwen3-30B-A3B when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, Llama 3.3 70B or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper on tracked token pricing. Llama 3.3 70B costs $0.9/1M input and $0.9/1M output tokens. Qwen3-30B-A3B costs $0.08/1M input and $0.28/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.3 70B or Qwen3-30B-A3B open source?
Llama 3.3 70B is listed under True. Qwen3-30B-A3B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Llama 3.3 70B or Qwen3-30B-A3B?
Llama 3.3 70B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Llama 3.3 70B or Qwen3-30B-A3B?
Llama 3.3 70B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, Llama 3.3 70B or Qwen3-30B-A3B?
Llama 3.3 70B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.3 70B and Qwen3-30B-A3B?
Llama 3.3 70B is available on Fireworks AI. Qwen3-30B-A3B is available on OpenRouter, Fireworks AI, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.