Llama 4 Maverick 17B Instruct FP8 vs Qwen2-7B-Instruct
Llama 4 Maverick 17B Instruct FP8 (2025) and Qwen2-7B-Instruct (2024) are compact production models from AI at Meta and Alibaba. Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window, while Qwen2-7B-Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 4 Maverick 17B Instruct FP8 fits 8x more tokens; pick it for long-context work and Qwen2-7B-Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 4 Maverick 17B Instruct FP8 | Qwen2-7B-Instruct |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 1m | 128k |
| Cheapest output | $0.60/1M tokens | - |
| Provider routes | 10 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
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 broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Maverick 17B Instruct FP8 uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.
- Local decision data tags Qwen2-7B-Instruct for Long context.
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
Qwen2-7B-Instruct
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Llama 4 Maverick 17B Instruct FP8 adds Vision, Multimodal, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2024-06-07 |
| Context window | 1m | 128k |
| Parameters | 400B (17B active) | 7B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Llama 4 Community | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Qwen2-7B-Instruct |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.60/1M tokens | - |
| Providers |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Qwen2-7B-Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: Llama 4 Maverick 17B Instruct FP8, multimodal input: Llama 4 Maverick 17B Instruct FP8, and structured outputs: Llama 4 Maverick 17B Instruct FP8. 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 4 Maverick 17B Instruct FP8 has $0.15/1M input tokens and Qwen2-7B-Instruct has no token price sourced yet. Provider availability is 10 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Qwen2-7B-Instruct when provider fit 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 4 Maverick 17B Instruct FP8 or Qwen2-7B-Instruct?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while Qwen2-7B-Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 4 Maverick 17B Instruct FP8 or Qwen2-7B-Instruct open source?
Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 Community. Qwen2-7B-Instruct 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 Qwen2-7B-Instruct?
Llama 4 Maverick 17B Instruct FP8 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 4 Maverick 17B Instruct FP8 or Qwen2-7B-Instruct?
Llama 4 Maverick 17B Instruct FP8 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 structured outputs, Llama 4 Maverick 17B Instruct FP8 or Qwen2-7B-Instruct?
Llama 4 Maverick 17B Instruct FP8 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 4 Maverick 17B Instruct FP8 and Qwen2-7B-Instruct?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Qwen2-7B-Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.