LLM Reference

GPT-4o Audio vs o1 (12-17)

GPT-4o Audio (2024) and o1 (12-17) (2024) are frontier reasoning models from OpenAI. GPT-4o Audio ships a 128k-token context window, while o1 (12-17) ships a 128k-token context window. On pricing, GPT-4o Audio costs $2.50/1M input tokens versus $15/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

GPT-4o Audio is ~500% cheaper at $2.50/1M; pay for o1 (12-17) only for coding workflow support.

Decision scorecard

Local evidence first
SignalGPT-4o Audioo1 (12-17)
Best forgeneral production evaluationreasoning-heavy apps and provider-routed production
Decision fitLong contextCoding, Agents, and Long context
Context window128k128k
Cheapest output$10/1M tokens$60/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose GPT-4o Audio when...
  • GPT-4o Audio has the lower cheapest tracked output price at $10/1M tokens.
  • Local decision data tags GPT-4o Audio for Long context.
Choose o1 (12-17) when...
  • o1 (12-17) has broader tracked provider coverage for fallback and procurement flexibility.
  • o1 (12-17) uniquely exposes Reasoning and Code execution in local model data.
  • Local decision data tags o1 (12-17) for Coding, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate GPT-4o Audio

GPT-4o Audio

$4,500

Cheapest tracked route/tier: OpenRouter

o1 (12-17)

$27,000

Cheapest tracked route/tier: Replicate API

Estimated monthly gap: $22,500. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-4o Audio -> o1 (12-17)
  • No overlapping tracked provider route is sourced for GPT-4o Audio and o1 (12-17); plan for SDK, billing, or endpoint changes.
  • o1 (12-17) is $50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • o1 (12-17) adds Reasoning and Code execution in local capability data.
o1 (12-17) -> GPT-4o Audio
  • No overlapping tracked provider route is sourced for o1 (12-17) and GPT-4o Audio; plan for SDK, billing, or endpoint changes.
  • GPT-4o Audio is $50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Reasoning and Code execution before moving production traffic.

Specs

Specification
Released2024-10-012024-12-17
Context window128k128k
Parameters
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2023-10-

Pricing and availability

Pricing attributeGPT-4o Audioo1 (12-17)
Input price$2.50/1M tokens$15/1M tokens
Output price$10/1M tokens$60/1M tokens
Providers

Capabilities

CapabilityGPT-4o Audioo1 (12-17)
VisionNoNo
MultimodalNoNo
ReasoningNoYes
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on reasoning mode: o1 (12-17) and code execution: o1 (12-17). 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 $2.50/1M input and $10/1M output tokens on the cheapest tracked provider, while o1 (12-17) lists $15/1M input and $60/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-4o Audio lower by about $23.75 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose GPT-4o Audio when provider fit and lower input-token cost are central to the workload. Choose o1 (12-17) when coding workflow support 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.

FAQ

Which has a larger context window, GPT-4o Audio or o1 (12-17)?

GPT-4o Audio supports 128k tokens, while o1 (12-17) 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 o1 (12-17)?

GPT-4o Audio is cheaper on tracked token pricing. GPT-4o Audio costs $2.50/1M input and $10/1M output tokens. o1 (12-17) costs $15/1M input and $60/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-4o Audio or o1 (12-17) open source?

GPT-4o Audio is listed under Proprietary. o1 (12-17) 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-4o Audio or o1 (12-17)?

o1 (12-17) 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 code execution, GPT-4o Audio or o1 (12-17)?

o1 (12-17) has the clearer documented code execution signal in this comparison. If code execution 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 o1 (12-17)?

GPT-4o Audio is available on OpenRouter. o1 (12-17) is available on Replicate API and OpenAI API. 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: 2026-06-15. Data sourced from public model cards and provider documentation.