Firefunction V1 vs Qwen3.5-9B
Firefunction V1 (2024) and Qwen3.5-9B (2026) are compact production models from Fireworks AI and Alibaba. Firefunction V1 ships a 8K-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 $0.5/1M 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 ~400% cheaper at $0.1/1M; pay for Firefunction V1 only for provider fit.
Decision scorecard
Local evidence first| Signal | Firefunction V1 | Qwen3.5-9B |
|---|---|---|
| Decision fit | General | RAG, Agents, and Long context |
| Context window | 8K | 262K |
| Cheapest output | $0.5/1M tokens | $0.15/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Use Firefunction V1 when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling 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.
Firefunction V1
$525
Cheapest tracked route: Fireworks AI
Qwen3.5-9B
$118
Cheapest tracked route: Together AI
Estimated monthly gap: $408. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Firefunction V1 and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-9B is $0.35/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-9B and Firefunction V1; plan for SDK, billing, or endpoint changes.
- Firefunction V1 is $0.35/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-01-29 | 2026-03-02 |
| Context window | 8K | 262K |
| Parameters | 46B | 9B |
| Architecture | decoder only | decoder only |
| License | Unknown | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Firefunction V1 | Qwen3.5-9B |
|---|---|---|
| Input price | $0.5/1M tokens | $0.1/1M tokens |
| Output price | $0.5/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Firefunction V1 | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | 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, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, tool use: Qwen3.5-9B, and structured outputs: Qwen3.5-9B. 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.
For cost, Firefunction V1 lists $0.5/1M input and $0.5/1M 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 $0.39 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.
Choose Firefunction V1 when provider fit are central to the workload. Choose Qwen3.5-9B when long-context analysis, larger context windows, 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.
FAQ
Which has a larger context window, Firefunction V1 or Qwen3.5-9B?
Qwen3.5-9B supports 262K tokens, while Firefunction V1 supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Firefunction V1 or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Firefunction V1 costs $0.5/1M input and $0.5/1M 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 Firefunction V1 or Qwen3.5-9B open source?
Firefunction V1 is listed under Unknown. 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, Firefunction V1 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, Firefunction V1 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 Firefunction V1 and Qwen3.5-9B?
Firefunction V1 is available on Fireworks AI. 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.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.