Llama 3 70B Instruct vs Qwen3.6-35B-A3B
Llama 3 70B Instruct (2024) and Qwen3.6-35B-A3B (2026) are agentic coding models from AI at Meta and Alibaba. Llama 3 70B Instruct ships a 8K-token context window, while Qwen3.6-35B-A3B ships a 262K-token context window. On MMLU PRO, Qwen3.6-35B-A3B leads by 27.8 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.6-35B-A3B fits 33x more tokens; pick it for long-context work and Llama 3 70B Instruct for tighter calls.
Specs
| Released | 2024-04-18 | 2026-04-16 |
| Context window | 8K | 262K |
| Parameters | 70B | 35 |
| Architecture | decoder only | moe |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 3 70B Instruct | Qwen3.6-35B-A3B | |
|---|---|---|
| Input price | $0.4/1M tokens | - |
| Output price | $0.4/1M tokens | - |
| Providers | - |
Capabilities
| Llama 3 70B Instruct | Qwen3.6-35B-A3B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 70B Instruct | Qwen3.6-35B-A3B |
|---|---|---|
| MMLU PRO | 57.4 | 85.2 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 70B Instruct at 57.4 and Qwen3.6-35B-A3B at 85.2, with Qwen3.6-35B-A3B ahead by 27.8 points. The largest visible gap is 27.8 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on multimodal input: Qwen3.6-35B-A3B, function calling: Qwen3.6-35B-A3B, tool use: Qwen3.6-35B-A3B, and structured outputs: Llama 3 70B Instruct. 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.
Pricing coverage is uneven: Llama 3 70B Instruct has $0.4/1M input tokens and Qwen3.6-35B-A3B has no token price sourced yet. Provider availability is 18 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3 70B Instruct when provider fit and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 3 70B Instruct or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B supports 262K tokens, while Llama 3 70B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3 70B Instruct or Qwen3.6-35B-A3B open source?
Llama 3 70B Instruct is listed under Open Source. Qwen3.6-35B-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 multimodal input, Llama 3 70B Instruct or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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 70B Instruct or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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.
Which is better for tool use, Llama 3 70B Instruct or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the clearer documented tool use signal in this comparison. If tool use 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 70B Instruct and Qwen3.6-35B-A3B?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Qwen3.6-35B-A3B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.