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GPT-4o Audio vs Mistral Large 2

GPT-4o Audio (2024) and Mistral Large 2 (2025) are compact production models from OpenAI and MistralAI. GPT-4o Audio ships a 128K-token context window, while Mistral Large 2 ships a 128K-token context window. On pricing, Mistral Large 2 costs $0.48/1M 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.

Mistral Large 2 is ~421% cheaper at $0.48/1M; pay for GPT-4o Audio only for provider fit.

Specs

Specification
Released2024-10-012025-11-25
Context window128K128K
Parameters123B
Architecturedecoder onlydecoder only
LicenseUnknownTrue
Knowledge cutoff-2025-07

Pricing and availability

Pricing attributeGPT-4o AudioMistral Large 2
Input price$2.5/1M tokens$0.48/1M tokens
Output price$10/1M tokens$2.4/1M tokens
Providers

Capabilities

CapabilityGPT-4o AudioMistral Large 2
VisionNoYes
MultimodalNoYes
ReasoningNoNo
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: Mistral Large 2, multimodal input: Mistral Large 2, function calling: Mistral Large 2, tool use: Mistral Large 2, and structured outputs: Mistral Large 2. 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 Mistral Large 2 lists $0.48/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large 2 lower by about $3.69 per million blended tokens. Availability is 1 providers versus 4, so concentration risk also matters.

Choose GPT-4o Audio when provider fit are central to the workload. Choose Mistral Large 2 when vision-heavy evaluation, lower input-token cost, 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.

FAQ

Which has a larger context window, GPT-4o Audio or Mistral Large 2?

GPT-4o Audio supports 128K tokens, while Mistral Large 2 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 Mistral Large 2?

Mistral Large 2 is cheaper on tracked token pricing. GPT-4o Audio costs $2.5/1M input and $10/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-4o Audio or Mistral Large 2 open source?

GPT-4o Audio is listed under Unknown. Mistral Large 2 is listed under True. 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 Mistral Large 2?

Mistral Large 2 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.

Which is better for multimodal input, GPT-4o Audio or Mistral Large 2?

Mistral Large 2 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 Mistral Large 2?

GPT-4o Audio is available on OpenRouter. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.