GPT-4 Turbo (older v1106) vs Qwen3.5-9B
GPT-4 Turbo (older v1106) (2023) and Qwen3.5-9B (2026) are compact production models from OpenAI and Alibaba. GPT-4 Turbo (older v1106) ships a 128k-token context window, while Qwen3.5-9B ships a 262k-token context window. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $10/1M 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 ~9900% cheaper at $0.10/1M; pay for GPT-4 Turbo (older v1106) only for provider fit.
Decision scorecard
Local evidence first| Signal | GPT-4 Turbo (older v1106) | Qwen3.5-9B |
|---|---|---|
| Best for | general production evaluation | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | RAG, Long context, and Classification | RAG, Agents, and Long context |
| Context window | 128k | 262k |
| Cheapest output | $30/1M tokens | $0.15/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags GPT-4 Turbo (older v1106) for RAG, Long context, and Classification.
- 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 route or tier on this page.
GPT-4 Turbo (older v1106)
$15,500
Cheapest tracked route/tier: OpenRouter
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $15,383. Batch, cache, alternate speed tiers, 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 $29.85/1M 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.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-4 Turbo (older v1106) is $29.85/1M 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 | 2023-11-06 | 2026-03-02 |
| Context window | 128k | 262k |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Unknown | Apache 2.0 |
| Knowledge cutoff | 2023-04 | - |
Pricing and availability
| Pricing attribute | GPT-4 Turbo (older v1106) | Qwen3.5-9B |
|---|---|---|
| Input price | $10/1M tokens | $0.10/1M tokens |
| Output price | $30/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | GPT-4 Turbo (older v1106) | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| 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
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, and tool use: Qwen3.5-9B. Both models share 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, GPT-4 Turbo (older v1106) lists $10/1M input and $30/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M 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 $15.88 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.
Choose GPT-4 Turbo (older v1106) 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, GPT-4 Turbo (older v1106) or Qwen3.5-9B?
Qwen3.5-9B supports 262k tokens, while GPT-4 Turbo (older v1106) supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-4 Turbo (older v1106) or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. GPT-4 Turbo (older v1106) costs $10/1M input and $30/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-4 Turbo (older v1106) or Qwen3.5-9B open source?
GPT-4 Turbo (older v1106) 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, GPT-4 Turbo (older v1106) 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, GPT-4 Turbo (older v1106) 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 GPT-4 Turbo (older v1106) and Qwen3.5-9B?
GPT-4 Turbo (older v1106) is available on OpenRouter. 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.