GPT-5.3-Codex vs Together AI Qwen2-72B-Instruct
GPT-5.3-Codex (2026) and Together AI Qwen2-72B-Instruct (2024) are agentic coding models from OpenAI and Alibaba. GPT-5.3-Codex ships a not-yet-sourced context window, while Together AI Qwen2-72B-Instruct ships a 33K-token context window. On pricing, Together AI Qwen2-72B-Instruct costs $0.7/1M input tokens versus $1.75/1M 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 is ~150% cheaper at $0.7/1M; pay for GPT-5.3-Codex only for coding workflow support.
Specs
| Released | 2026-02-05 | 2024-06-07 |
| Context window | — | 33K |
| Parameters | — | 72B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| GPT-5.3-Codex | Together AI Qwen2-72B-Instruct | |
|---|---|---|
| Input price | $1.75/1M tokens | $0.7/1M tokens |
| Output price | $14/1M tokens | $0.7/1M tokens |
| Providers |
Capabilities
| GPT-5.3-Codex | Together AI Qwen2-72B-Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: GPT-5.3-Codex, function calling: GPT-5.3-Codex, tool use: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. 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-5.3-Codex lists $1.75/1M input and $14/1M 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 Together AI Qwen2-72B-Instruct lower by about $4.72 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose GPT-5.3-Codex when coding workflow support are central to the workload. Choose Together AI Qwen2-72B-Instruct when provider fit 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 is cheaper, GPT-5.3-Codex or Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M 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 GPT-5.3-Codex or Together AI Qwen2-72B-Instruct open source?
GPT-5.3-Codex is listed under Proprietary. 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 multimodal input, GPT-5.3-Codex or Together AI Qwen2-72B-Instruct?
GPT-5.3-Codex 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.
Which is better for function calling, GPT-5.3-Codex or Together AI Qwen2-72B-Instruct?
GPT-5.3-Codex has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, GPT-5.3-Codex or Together AI Qwen2-72B-Instruct?
GPT-5.3-Codex has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Together AI Qwen2-72B-Instruct?
GPT-5.3-Codex is available on OpenRouter. 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.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.