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GPT-4o Audio vs Grok 4.3

GPT-4o Audio (2024) and Grok 4.3 (2026) are frontier reasoning models from OpenAI and xAI. GPT-4o Audio ships a 128K-token context window, while Grok 4.3 ships a 1M-token context window. On pricing, Grok 4.3 costs $1.25/1M input tokens versus $2.5/1M 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.

Grok 4.3 is ~100% cheaper at $1.25/1M; pay for GPT-4o Audio only for provider fit.

Specs

Specification
Released2024-10-012026-04-30
Context window128K1M
Parameters~0.5T
Architecturedecoder only-
LicenseUnknownProprietary
Knowledge cutoff--

Pricing and availability

Pricing attributeGPT-4o AudioGrok 4.3
Input price$2.5/1M tokens$1.25/1M tokens
Output price$10/1M tokens$2.5/1M tokens
Providers

Capabilities

CapabilityGPT-4o AudioGrok 4.3
VisionNoYes
MultimodalNoYes
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Grok 4.3, multimodal input: Grok 4.3, reasoning mode: Grok 4.3, function calling: Grok 4.3, tool use: Grok 4.3, and structured outputs: Grok 4.3. Both models share the core language-model surface, 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 Audio lists $2.5/1M input and $10/1M output tokens, while Grok 4.3 lists $1.25/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Grok 4.3 lower by about $3.13 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose GPT-4o Audio when provider fit are central to the workload. Choose Grok 4.3 when reasoning depth, 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. 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.

FAQ

Which has a larger context window, GPT-4o Audio or Grok 4.3?

Grok 4.3 supports 1M tokens, while GPT-4o Audio supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, GPT-4o Audio or Grok 4.3?

Grok 4.3 is cheaper on tracked token pricing. GPT-4o Audio costs $2.5/1M input and $10/1M output tokens. Grok 4.3 costs $1.25/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-4o Audio or Grok 4.3 open source?

GPT-4o Audio is listed under Unknown. Grok 4.3 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 vision, GPT-4o Audio or Grok 4.3?

Grok 4.3 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-4o Audio or Grok 4.3?

Grok 4.3 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.

Where can I run GPT-4o Audio and Grok 4.3?

GPT-4o Audio is available on OpenRouter. Grok 4.3 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: 2026-05-11. Data sourced from public model cards and provider documentation.