Llama 3 8B Instruct vs Qwen3.5-27B
Llama 3 8B Instruct (2024) and Qwen3.5-27B (2026) are frontier reasoning models from AI at Meta and Alibaba. Llama 3 8B Instruct ships a 8K-token context window, while Qwen3.5-27B ships a 262K-token context window. On Google-Proof Q&A, Qwen3.5-27B leads by 41 pts. On pricing, Llama 3 8B Instruct costs $0.03/1M input tokens versus $0.2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 8B Instruct is ~550% cheaper at $0.03/1M; pay for Qwen3.5-27B only for reasoning depth.
Specs
| Released | 2024-04-18 | 2026-02-24 |
| Context window | 8K | 262K |
| Parameters | 8B | 27B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 3 8B Instruct | Qwen3.5-27B | |
|---|---|---|
| Input price | $0.03/1M tokens | $0.2/1M tokens |
| Output price | $0.04/1M tokens | $1.56/1M tokens |
| Providers |
Capabilities
| Llama 3 8B Instruct | Qwen3.5-27B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 8B Instruct | Qwen3.5-27B |
|---|---|---|
| Google-Proof Q&A | 44.8 | 85.8 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 3 8B Instruct at 44.8 and Qwen3.5-27B at 85.8, with Qwen3.5-27B ahead by 41 points. The largest visible gap is 41 points on Google-Proof Q&A, 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 reasoning mode: Qwen3.5-27B, function calling: Qwen3.5-27B, and tool use: Qwen3.5-27B. Both models share structured outputs, 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 8B Instruct lists $0.03/1M input and $0.04/1M output tokens, while Qwen3.5-27B lists $0.2/1M input and $1.56/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.57 per million blended tokens. Availability is 17 providers versus 1, so concentration risk also matters.
Choose Llama 3 8B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3.5-27B when reasoning depth 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 8B Instruct or Qwen3.5-27B?
Qwen3.5-27B supports 262K tokens, while Llama 3 8B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 3 8B Instruct or Qwen3.5-27B?
Llama 3 8B Instruct is cheaper on tracked token pricing. Llama 3 8B Instruct costs $0.03/1M input and $0.04/1M output tokens. Qwen3.5-27B costs $0.2/1M input and $1.56/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 8B Instruct or Qwen3.5-27B open source?
Llama 3 8B Instruct is listed under Open Source. Qwen3.5-27B 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 reasoning mode, Llama 3 8B Instruct or Qwen3.5-27B?
Qwen3.5-27B has the clearer documented reasoning mode signal in this comparison. If reasoning mode 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 8B Instruct or Qwen3.5-27B?
Qwen3.5-27B 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 8B Instruct and Qwen3.5-27B?
Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Qwen3.5-27B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.