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GPT-5.3-Codex-Spark vs Grok 4.20

GPT-5.3-Codex-Spark (2026) and Grok 4.20 (2026) are agentic coding models from OpenAI and xAI. GPT-5.3-Codex-Spark ships a 131K-token context window, while Grok 4.20 ships a 2M-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Grok 4.20 fits 15x more tokens; pick it for long-context work and GPT-5.3-Codex-Spark for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-5.3-Codex-SparkGrok 4.20
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window131K2M
Cheapest output-$2.5/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.3-Codex-Spark when...
  • 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.
Choose Grok 4.20 when...
  • Grok 4.20 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Grok 4.20 has broader tracked provider coverage for fallback and procurement flexibility.
  • Grok 4.20 uniquely exposes Reasoning in local model data.
  • Local decision data tags Grok 4.20 for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

GPT-5.3-Codex-Spark

Unavailable

No complete token price in local provider data

Grok 4.20

$1,625

Cheapest tracked route: xAI Console

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

GPT-5.3-Codex-Spark -> Grok 4.20
  • No overlapping tracked provider route is sourced for GPT-5.3-Codex-Spark and Grok 4.20; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Code execution before moving production traffic.
  • Grok 4.20 adds Reasoning in local capability data.
Grok 4.20 -> GPT-5.3-Codex-Spark
  • No overlapping tracked provider route is sourced for Grok 4.20 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 Code execution in local capability data.

Specs

Specification
Released2026-02-122026-01-01
Context window131K2M
Parameters
Architecturedecoder only-
LicenseProprietaryProprietary
Knowledge cutoff--

Pricing and availability

Pricing attributeGPT-5.3-Codex-SparkGrok 4.20
Input price-$1.25/1M tokens
Output price-$2.5/1M tokens
Providers

Capabilities

CapabilityGPT-5.3-Codex-SparkGrok 4.20
VisionNoNo
MultimodalNoNo
ReasoningNoYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Grok 4.20 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 Grok 4.20 has $1.25/1M input tokens. Provider availability is 1 tracked routes versus 2. 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 Grok 4.20 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 Grok 4.20?

Grok 4.20 supports 2M 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 Grok 4.20 open source?

GPT-5.3-Codex-Spark is listed under Proprietary. Grok 4.20 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 Grok 4.20?

Grok 4.20 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 Grok 4.20?

Both GPT-5.3-Codex-Spark and Grok 4.20 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 Grok 4.20?

Both GPT-5.3-Codex-Spark and Grok 4.20 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 Grok 4.20?

GPT-5.3-Codex-Spark is available on OpenAI API. Grok 4.20 is available on xAI Console and 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.