GPT-5.3-Codex-Spark vs Tencent Hy3 Preview
GPT-5.3-Codex-Spark (2026) and Tencent Hy3 Preview (2026) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex-Spark ships a 131k-token context window, while Tencent Hy3 Preview 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 Tencent Hy3 Preview 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 | Tencent Hy3 Preview |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | reasoning-heavy apps and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 131k | 262k |
| Cheapest output | - | $0.26/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.3-Codex-Spark uniquely exposes Structured outputs and Code execution in local model data.
- Local decision data tags GPT-5.3-Codex-Spark for Coding, RAG, and Agents.
- Tencent Hy3 Preview has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Tencent Hy3 Preview uniquely exposes Reasoning in local model data.
- Local decision data tags Tencent Hy3 Preview 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
Tencent Hy3 Preview
$118
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 Tencent Hy3 Preview; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs and Code execution before moving production traffic.
- Tencent Hy3 Preview adds Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Tencent Hy3 Preview and GPT-5.3-Codex-Spark; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- GPT-5.3-Codex-Spark adds Structured outputs and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-12 | 2026-04-22 |
| Context window | 131k | 262k |
| Parameters | — | 295B |
| Architecture | decoder only | dense moe hybrid |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex-Spark | Tencent Hy3 Preview |
|---|---|---|
| Input price | - | $0.07/1M tokens |
| Output price | - | $0.26/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex-Spark | Tencent Hy3 Preview |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| 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 reasoning mode: Tencent Hy3 Preview, structured outputs: GPT-5.3-Codex-Spark, and code execution: GPT-5.3-Codex-Spark. Both models share function calling and tool use, 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 Tencent Hy3 Preview has $0.07/1M input tokens. Provider availability is 1 tracked routes versus 1. 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 Tencent Hy3 Preview when reasoning depth 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, GPT-5.3-Codex-Spark or Tencent Hy3 Preview?
Tencent Hy3 Preview 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.
Is GPT-5.3-Codex-Spark or Tencent Hy3 Preview open source?
GPT-5.3-Codex-Spark is listed under Proprietary. Tencent Hy3 Preview is listed under Proprietary. 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 reasoning mode, GPT-5.3-Codex-Spark or Tencent Hy3 Preview?
Tencent Hy3 Preview 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.
Which is better for function calling, GPT-5.3-Codex-Spark or Tencent Hy3 Preview?
Both GPT-5.3-Codex-Spark and Tencent Hy3 Preview expose function calling. 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 tool use, GPT-5.3-Codex-Spark or Tencent Hy3 Preview?
Both GPT-5.3-Codex-Spark and Tencent Hy3 Preview expose tool use. 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-5.3-Codex-Spark and Tencent Hy3 Preview?
GPT-5.3-Codex-Spark is available on OpenAI API. Tencent Hy3 Preview is available on OpenRouter. 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: 2026-05-14. Data sourced from public model cards and provider documentation.