Grok Code Fast 1 vs Qwen3.5-9B
Grok Code Fast 1 (2025) and Qwen3.5-9B (2026) are agentic coding models from xAI and Alibaba. Grok Code Fast 1 ships a 262K-token context window, while Qwen3.5-9B ships a 262K-token context window. On pricing, Qwen3.5-9B costs $0.1/1M input tokens versus $0.2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-9B is ~100% cheaper at $0.1/1M; pay for Grok Code Fast 1 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Grok Code Fast 1 | Qwen3.5-9B |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 262K | 262K |
| Cheapest output | $1.5/1M tokens | $0.15/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Grok Code Fast 1 for Coding, RAG, and Agents.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Grok Code Fast 1
$535
Cheapest tracked route: OpenRouter
Qwen3.5-9B
$118
Cheapest tracked route: Together AI
Estimated monthly gap: $418. 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.
- Qwen3.5-9B is $1.35/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Grok Code Fast 1 is $1.35/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-27 | 2026-03-02 |
| Context window | 262K | 262K |
| Parameters | 314B | 9B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Grok Code Fast 1 | Qwen3.5-9B |
|---|---|---|
| Input price | $0.2/1M tokens | $0.1/1M tokens |
| Output price | $1.5/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Grok Code Fast 1 | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | 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: Qwen3.5-9B and multimodal input: Qwen3.5-9B. Both models share function calling, tool use, 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, Grok Code Fast 1 lists $0.2/1M input and $1.5/1M output tokens, while Qwen3.5-9B lists $0.1/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $0.47 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Grok Code Fast 1 when coding workflow support are central to the workload. Choose Qwen3.5-9B when vision-heavy evaluation and lower input-token cost 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Grok Code Fast 1 or Qwen3.5-9B?
Grok Code Fast 1 supports 262K tokens, while Qwen3.5-9B supports 262K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Grok Code Fast 1 or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Grok Code Fast 1 costs $0.2/1M input and $1.5/1M output tokens. Qwen3.5-9B costs $0.1/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Grok Code Fast 1 or Qwen3.5-9B open source?
Grok Code Fast 1 is listed under Proprietary. Qwen3.5-9B 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, Grok Code Fast 1 or Qwen3.5-9B?
Qwen3.5-9B 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, Grok Code Fast 1 or Qwen3.5-9B?
Qwen3.5-9B 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 Grok Code Fast 1 and Qwen3.5-9B?
Grok Code Fast 1 is available on OpenRouter, Microsoft Foundry, and xAI Console. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-20. Data sourced from public model cards and provider documentation.