GPT-4o (08-06) vs Qwen3.5-9B

Name: GPT-4o (08-06)
Author: OpenAI

GPT-4o (08-06) (2024) and Qwen3.5-9B (2026) are compact production models from OpenAI and Alibaba. GPT-4o (08-06) ships a 128k-token context window, while Qwen3.5-9B ships a 262k-token context window. On MMLU PRO, Qwen3.5-9B leads by 7.8 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $2.50/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Qwen3.5-9B is ~2400% cheaper at $0.10/1M; pay for GPT-4o (08-06) only for coding workflow support.

Decision scorecard

Local evidence first

Signal	GPT-4o (08-06)	Qwen3.5-9B	How to read it
Best for	multimodal apps and provider-routed production	multimodal apps, tool-calling agents, and provider-routed production	Use-case synthesis from product type, capability flags, context, and provider data.
Decision fit	Coding, RAG, and Agents	RAG, Agents, and Long context	Primary workload tags from local decision data.
Context window	128k	262k	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$10/1M tokens	$0.15/1M tokens	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	3 tracked	3 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	1 rows	MMLU PRO leader	Largest visible lead is 7.8 points on MMLU PRO.

Decision tradeoffs

Choose GPT-4o (08-06) when...

GPT-4o (08-06) uniquely exposes Code execution in local model data.
Local decision data tags GPT-4o (08-06) for Coding, RAG, and Agents.

Choose Qwen3.5-9B when...

Qwen3.5-9B leads the largest shared benchmark signal on MMLU PRO by 7.8 points.
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 uniquely exposes Function calling and Tool use 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.

Lower estimate Qwen3.5-9B

Requests / monthInput tokens / requestOutput tokens / request

GPT-4o (08-06)

$4,500

Cheapest tracked route/tier: OpenAI API

Qwen3.5-9B

$118

Cheapest tracked route/tier: Together AI

Estimated monthly gap: $4,383. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-4o (08-06) -> Qwen3.5-9B

Provider overlap exists on OpenRouter; start route-level A/B tests there.
Qwen3.5-9B is $9.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Check replacement coverage for Code execution before moving production traffic.
Qwen3.5-9B adds Function calling and Tool use in local capability data.

Qwen3.5-9B -> GPT-4o (08-06)

Provider overlap exists on OpenRouter; start route-level A/B tests there.
GPT-4o (08-06) is $9.85/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Check replacement coverage for Function calling and Tool use before moving production traffic.
GPT-4o (08-06) adds Code execution in local capability data.

Specs

Specification	GPT-4o (08-06) OpenAI	Qwen3.5-9B Alibaba
Released	2024-08-06	2026-03-02
Context window	128k	262k
Parameters	1.76T (8x222B MoE)*	9B
Architecture	mixture of experts	decoder only
License	Proprietary	Apache 2.0
Knowledge cutoff	2023-10	-

Pricing and availability

Pricing attribute	GPT-4o (08-06)	Qwen3.5-9B
Input price	$2.50/1M tokens	$0.10/1M tokens
Output price	$10/1M tokens	$0.15/1M tokens
Providers	OpenAI API Salesforce Einstein Generative AI OpenRouter	Together AI OpenRouter Alibaba Cloud PAI-EAS

Capabilities

Capability	GPT-4o (08-06)	Qwen3.5-9B
Vision	Yes	Yes
Multimodal	Yes	Yes
Reasoning	No	No
Function calling	No	Yes
Tool use	No	Yes
Structured outputs	Yes	Yes
Code execution	Yes	No
IDE integration	No	No
Computer use	No	No
Parallel agents	No	No

Benchmarks

Benchmark	GPT-4o (08-06)	Qwen3.5-9B
MMLU PRO	74.7	82.5

Deep dive

On shared benchmark coverage, MMLU PRO has GPT-4o (08-06) at 74.7 and Qwen3.5-9B at 82.5, with Qwen3.5-9B ahead by 7.8 points. The largest visible gap is 7.8 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on function calling: Qwen3.5-9B, tool use: Qwen3.5-9B, and code execution: GPT-4o (08-06). Both models share vision, multimodal input, 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, GPT-4o (08-06) lists $2.50/1M input and $10/1M 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 $4.63 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.

Choose GPT-4o (08-06) when coding workflow support 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.

FAQ

Which has a larger context window, GPT-4o (08-06) or Qwen3.5-9B?

Qwen3.5-9B supports 262k tokens, while GPT-4o (08-06) supports 128k 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, GPT-4o (08-06) or Qwen3.5-9B?

Qwen3.5-9B is cheaper on tracked token pricing. GPT-4o (08-06) costs $2.50/1M input and $10/1M 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-4o (08-06) or Qwen3.5-9B open source?

GPT-4o (08-06) 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, GPT-4o (08-06) or Qwen3.5-9B?

Both GPT-4o (08-06) and Qwen3.5-9B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, GPT-4o (08-06) or Qwen3.5-9B?

Both GPT-4o (08-06) and Qwen3.5-9B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run GPT-4o (08-06) and Qwen3.5-9B?

GPT-4o (08-06) is available on OpenAI API, Salesforce Einstein Generative AI, and 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.

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Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.