Llama 4 Maverick 17B Instruct FP8 vs Qwen3.6 Max Preview
Llama 4 Maverick 17B Instruct FP8 (2025) and Qwen3.6 Max Preview (2026) are frontier reasoning models from AI at Meta and Alibaba. Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window, while Qwen3.6 Max Preview ships a 256k-token context window. On MMLU PRO, Qwen3.6 Max Preview leads by 8 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen3.6 Max Preview is safer overall; choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6 Max Preview |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 256k |
| Cheapest output | $0.60/1M tokens | $6.24/1M tokens |
| Provider routes | 10 tracked | 3 tracked |
| Shared benchmarks | 4 rows | MMLU PRO leader |
Decision tradeoffs
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has the lower cheapest tracked output price at $0.60/1M tokens.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.
- Qwen3.6 Max Preview holds a shared-benchmark lead on MMLU PRO, ahead by 8 points.
- Qwen3.6 Max Preview uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags Qwen3.6 Max Preview for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
Qwen3.6 Max Preview
$2,392
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $2,122. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Qwen3.6 Max Preview is $5.64/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.6 Max Preview adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Llama 4 Maverick 17B Instruct FP8 is $5.64/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-04-20 |
| Context window | 1m | 256k |
| Parameters | 400B (17B active) | — |
| Architecture | mixture of experts | moe |
| License | Llama 4 Community | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6 Max Preview |
|---|---|---|
| Input price | $0.15/1M tokens |
|
| Output price | $0.60/1M tokens |
|
| Providers |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6 Max Preview |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6 Max Preview |
|---|---|---|
| MMLU PRO | 80.5 | 88.5 |
| Google-Proof Q&A | 67.1 | 86.0 |
| LiveCodeBench | 43.4 | 87.1 |
| Massive Multi-discipline Multimodal Understanding | 73.4 | 82.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 4 Maverick 17B Instruct FP8 at 80.5 and Qwen3.6 Max Preview at 88.5, with Qwen3.6 Max Preview ahead by 8 points; Google-Proof Q&A has Llama 4 Maverick 17B Instruct FP8 at 67.1 and Qwen3.6 Max Preview at 86, with Qwen3.6 Max Preview ahead by 18.9 points; LiveCodeBench has Llama 4 Maverick 17B Instruct FP8 at 43.4 and Qwen3.6 Max Preview at 87.1, with Qwen3.6 Max Preview ahead by 43.7 points. The largest visible gap is 43.7 points on LiveCodeBench, 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: Qwen3.6 Max Preview, function calling: Qwen3.6 Max Preview, and tool use: Qwen3.6 Max Preview. Both models share vision, multimodal input, and 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 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.60/1M output tokens on the cheapest tracked provider, while Qwen3.6 Max Preview lists tiered pricing: 0-128,000t is $1.30/1M input and $7.80/1M output; 128,000t+ is $2/1M input and $12/1M output. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct FP8 lower by about $2.31 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 10 providers versus 3, so concentration risk also matters.
Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Qwen3.6 Max Preview when reasoning depth 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 4 Maverick 17B Instruct FP8 or Qwen3.6 Max Preview?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while Qwen3.6 Max Preview supports 256k 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 4 Maverick 17B Instruct FP8 or Qwen3.6 Max Preview?
Llama 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.60/1M output tokens on the cheapest tracked provider. Qwen3.6 Max Preview lists tiered pricing: 0-128,000t is $1.30/1M input and $7.80/1M output; 128,000t+ is $2/1M input and $12/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Llama 4 Maverick 17B Instruct FP8 or Qwen3.6 Max Preview open source?
Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 Community. Qwen3.6 Max Preview 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 4 Maverick 17B Instruct FP8 or Qwen3.6 Max Preview?
Both Llama 4 Maverick 17B Instruct FP8 and Qwen3.6 Max Preview expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Llama 4 Maverick 17B Instruct FP8 or Qwen3.6 Max Preview?
Both Llama 4 Maverick 17B Instruct FP8 and Qwen3.6 Max Preview expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 4 Maverick 17B Instruct FP8 and Qwen3.6 Max Preview?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Qwen3.6 Max Preview is available on OpenRouter, Alibaba Cloud PAI-EAS, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-07. Data sourced from public model cards and provider documentation.