Llama 3.1 70B Instruct vs Qwen3-Max
Llama 3.1 70B Instruct (2024) and Qwen3-Max (2026) are compact production models from AI at Meta and Alibaba. Llama 3.1 70B Instruct ships a 128K-token context window, while Qwen3-Max ships a 128K-token context window. On pricing, Llama 3.1 70B Instruct costs $0.4/1M input tokens versus $0.78/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.1 70B Instruct is ~95% cheaper at $0.4/1M; pay for Qwen3-Max only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Llama 3.1 70B Instruct | Qwen3-Max |
|---|---|---|
| Decision fit | Coding, RAG, and Long context | Coding, RAG, and Agents |
| Context window | 128K | 128K |
| Cheapest output | $0.4/1M tokens | $3.9/1M tokens |
| Provider routes | 11 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3.1 70B Instruct has the lower cheapest tracked output price at $0.4/1M tokens.
- Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, and Long context.
- Qwen3-Max uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Qwen3-Max for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.1 70B Instruct
$420
Cheapest tracked route: Hyperbolic AI Inference
Qwen3-Max
$1,599
Cheapest tracked route: OpenRouter
Estimated monthly gap: $1,179. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3-Max is $3.5/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3-Max adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Llama 3.1 70B Instruct is $3.5/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2026-01-15 |
| Context window | 128K | 128K |
| Parameters | 70B | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2023-12 | 2025-12 |
Pricing and availability
| Pricing attribute | Llama 3.1 70B Instruct | Qwen3-Max |
|---|---|---|
| Input price | $0.4/1M tokens | $0.78/1M tokens |
| Output price | $0.4/1M tokens | $3.9/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 70B Instruct | Qwen3-Max |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | 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: Qwen3-Max, multimodal input: Qwen3-Max, function calling: Qwen3-Max, and tool use: Qwen3-Max. 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 3.1 70B Instruct lists $0.4/1M input and $0.4/1M output tokens, while Qwen3-Max lists $0.78/1M input and $3.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.1 70B Instruct lower by about $1.32 per million blended tokens. Availability is 11 providers versus 1, so concentration risk also matters.
Choose Llama 3.1 70B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3-Max when vision-heavy evaluation 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 has a larger context window, Llama 3.1 70B Instruct or Qwen3-Max?
Llama 3.1 70B Instruct supports 128K tokens, while Qwen3-Max supports 128K 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 3.1 70B Instruct or Qwen3-Max?
Llama 3.1 70B Instruct is cheaper on tracked token pricing. Llama 3.1 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Qwen3-Max costs $0.78/1M input and $3.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.1 70B Instruct or Qwen3-Max open source?
Llama 3.1 70B Instruct is listed under Open Source. Qwen3-Max is listed under Proprietary. 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 3.1 70B Instruct or Qwen3-Max?
Qwen3-Max 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Llama 3.1 70B Instruct or Qwen3-Max?
Qwen3-Max 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.
Where can I run Llama 3.1 70B Instruct and Qwen3-Max?
Llama 3.1 70B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Qwen3-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.