Firefunction V1 vs Together AI Qwen2-72B-Instruct
Firefunction V1 (2024) and Together AI Qwen2-72B-Instruct (2024) are compact production models from Fireworks AI and Alibaba. Firefunction V1 ships a 8K-token context window, while Together AI Qwen2-72B-Instruct ships a 33K-token context window. On pricing, Firefunction V1 costs $0.5/1M input tokens versus $0.7/1M 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.
Together AI Qwen2-72B-Instruct fits 4x more tokens; pick it for long-context work and Firefunction V1 for tighter calls.
Decision scorecard
Local evidence first| Signal | Firefunction V1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Decision fit | General | Classification and JSON / Tool use |
| Context window | 8K | 33K |
| Cheapest output | $0.5/1M tokens | $0.7/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Firefunction V1 has the lower cheapest tracked output price at $0.5/1M tokens.
- Together AI Qwen2-72B-Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Together AI Qwen2-72B-Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Together AI Qwen2-72B-Instruct for Classification and JSON / Tool use.
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
Together AI Qwen2-72B-Instruct
$735
Cheapest tracked route: Together AI
Estimated monthly gap: $210. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Firefunction V1 and Together AI Qwen2-72B-Instruct; plan for SDK, billing, or endpoint changes.
- Together AI Qwen2-72B-Instruct is $0.2/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Together AI Qwen2-72B-Instruct adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Together AI Qwen2-72B-Instruct and Firefunction V1; plan for SDK, billing, or endpoint changes.
- Firefunction V1 is $0.2/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-01-29 | 2024-06-07 |
| Context window | 8K | 33K |
| Parameters | 46B | 72B |
| Architecture | decoder only | decoder only |
| License | Unknown | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Firefunction V1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Input price | $0.5/1M tokens | $0.7/1M tokens |
| Output price | $0.5/1M tokens | $0.7/1M tokens |
| Providers |
Capabilities
| Capability | Firefunction V1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| 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 structured outputs: Together AI Qwen2-72B-Instruct. 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 Together AI Qwen2-72B-Instruct lists $0.7/1M input and $0.7/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Firefunction V1 lower by about $0.2 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Firefunction V1 when provider fit and lower input-token cost are central to the workload. Choose Together AI Qwen2-72B-Instruct when long-context analysis and larger context windows 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, Firefunction V1 or Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct supports 33K 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.
Which is cheaper, Firefunction V1 or Together AI Qwen2-72B-Instruct?
Firefunction V1 is cheaper on tracked token pricing. Firefunction V1 costs $0.5/1M input and $0.5/1M output tokens. Together AI Qwen2-72B-Instruct costs $0.7/1M input and $0.7/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Firefunction V1 or Together AI Qwen2-72B-Instruct open source?
Firefunction V1 is listed under Unknown. Together AI Qwen2-72B-Instruct is listed under Open Source. 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 structured outputs, Firefunction V1 or Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct 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 Firefunction V1 and Together AI Qwen2-72B-Instruct?
Firefunction V1 is available on Fireworks AI. Together AI Qwen2-72B-Instruct is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Firefunction V1 over Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct fits 4x more tokens; pick it for long-context work and Firefunction V1 for tighter calls. If your workload also depends on provider fit, start with Firefunction V1; if it depends on long-context analysis, run the same evaluation with Together AI Qwen2-72B-Instruct.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.