GPT-5.3-Codex-Spark vs Qwen3.5-122B-A10B
GPT-5.3-Codex-Spark (2026) and Qwen3.5-122B-A10B (2026) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex-Spark ships a 131k-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GPT-5.3-Codex-Spark is coding-specialized model, while Qwen3.5-122B-A10B is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.3-Codex-Spark | Qwen3.5-122B-A10B |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 131k | 262k |
| Cheapest output | - | $2.08/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.3-Codex-Spark uniquely exposes Code execution in local model data.
- Local decision data tags GPT-5.3-Codex-Spark for Coding, RAG, and Agents.
- Qwen3.5-122B-A10B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-122B-A10B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-122B-A10B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.5-122B-A10B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.3-Codex-Spark
Unavailable
No complete token price in local provider data
Qwen3.5-122B-A10B
$728
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.3-Codex-Spark and Qwen3.5-122B-A10B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Code execution before moving production traffic.
- Qwen3.5-122B-A10B adds Vision, Multimodal, and Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-122B-A10B and GPT-5.3-Codex-Spark; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- GPT-5.3-Codex-Spark adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-12 | 2026-02-24 |
| Context window | 131k | 262k |
| Parameters | — | 122B |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex-Spark | Qwen3.5-122B-A10B |
|---|---|---|
| Input price | - | $0.26/1M tokens |
| Output price | - | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex-Spark | Qwen3.5-122B-A10B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | 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: Qwen3.5-122B-A10B, multimodal input: Qwen3.5-122B-A10B, reasoning mode: Qwen3.5-122B-A10B, and code execution: GPT-5.3-Codex-Spark. Both models share function calling, tool use, 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.
Pricing coverage is uneven: GPT-5.3-Codex-Spark has no token price sourced yet and Qwen3.5-122B-A10B has $0.26/1M input tokens. Provider availability is 1 tracked routes versus 3. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-5.3-Codex-Spark when coding workflow support are central to the workload. Choose Qwen3.5-122B-A10B when reasoning depth, larger context windows, and broader provider choice 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, GPT-5.3-Codex-Spark or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B supports 262k tokens, while GPT-5.3-Codex-Spark supports 131k 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.
Is GPT-5.3-Codex-Spark or Qwen3.5-122B-A10B open source?
GPT-5.3-Codex-Spark is listed under Proprietary. Qwen3.5-122B-A10B 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-5.3-Codex-Spark or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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-5.3-Codex-Spark or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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 reasoning mode, GPT-5.3-Codex-Spark or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B has the clearer documented reasoning mode signal in this comparison. If reasoning mode 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-Spark and Qwen3.5-122B-A10B?
GPT-5.3-Codex-Spark is available on OpenAI API. Qwen3.5-122B-A10B is available on OpenRouter, Alibaba Cloud PAI-EAS, and Novita 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: 2026-06-04. Data sourced from public model cards and provider documentation.