LLM Reference

GPT-4o (08-06) vs GPT-5.5

GPT-4o (08-06) (2024) and GPT-5.5 (2026) are frontier reasoning models from OpenAI. GPT-4o (08-06) ships a 128k-token context window, while GPT-5.5 ships a 1.05m-token context window. On MMLU PRO, GPT-5.5 leads by 13.4 pts. On pricing, GPT-4o (08-06) costs $2.50/1M input tokens; GPT-5.5 ranges from $5 to $8/1M input tokens by tier. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

GPT-5.5 fits 8x more tokens; pick it for long-context work and GPT-4o (08-06) for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-4o (08-06)GPT-5.5
Best formultimodal apps and provider-routed productionreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window128k1.05m
Cheapest output$10/1M tokens$30/1M tokens
Provider routes3 tracked3 tracked
Shared benchmarks2 rowsMMLU PRO leader

Decision tradeoffs

Choose GPT-4o (08-06) when...
  • GPT-4o (08-06) has the lower cheapest tracked output price at $10/1M tokens.
  • Local decision data tags GPT-4o (08-06) for Coding, RAG, and Agents.
Choose GPT-5.5 when...
  • GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 13.4 points.
  • GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-5.5 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
  • Local decision data tags GPT-5.5 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.

Lower estimate GPT-4o (08-06)

GPT-4o (08-06)

$4,500

Cheapest tracked route/tier: OpenAI API

GPT-5.5

$11,500

Cheapest tracked route/tier: OpenAI API 0-272K input tokens

Estimated monthly gap: $7,000. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-4o (08-06) -> GPT-5.5
Local recipe
  • Provider overlap exists on OpenAI API and OpenRouter; start route-level A/B tests there.
  • GPT-5.5 is $20/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • GPT-5.5 adds Reasoning, Function calling, and Tool use in local capability data.
  • Use this scaffold to explain when GPT-5.5 is worth the move for coding, agents, and structured API work.
  • Compare quality gains against the cheapest tracked output-token route before recommending a migration.
  • Call out prompt, JSON schema, and tool-call compatibility checks before production traffic moves.
Review migration path
GPT-5.5 -> GPT-4o (08-06)
  • Provider overlap exists on OpenAI API and OpenRouter; start route-level A/B tests there.
  • GPT-4o (08-06) is $20/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.

Specs

Specification
Released2024-08-062026-04-23
Context window128k1.05m
Parameters1.76T (8x222B MoE)*
Architecturemixture of expertsdecoder only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
Commercial useCommercial use with conditionsCommercial use with conditions
Knowledge cutoff2023-102025-12

Pricing and availability

Pricing attributeGPT-4o (08-06)GPT-5.5
Input price$2.50/1M tokens
0-272K input tokens
$5/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
272K+ input tokens
$8/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
Output price$10/1M tokens
0-272K input tokens
$30/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
272K+ input tokens
$36/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
Providers

Capabilities

CapabilityGPT-4o (08-06)GPT-5.5
VisionYesYes
MultimodalYesYes
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsYesYes
Code executionYesYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGPT-4o (08-06)GPT-5.5
MMLU PRO74.788.1
Aider Polyglot23.188.0

Deep dive

On shared benchmark coverage, MMLU PRO has GPT-4o (08-06) at 74.7 and GPT-5.5 at 88.1, with GPT-5.5 ahead by 13.4 points; Aider Polyglot has GPT-4o (08-06) at 23.1 and GPT-5.5 at 88, with GPT-5.5 ahead by 64.9 points. The largest visible gap is 64.9 points on Aider Polyglot, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on reasoning mode: GPT-5.5, function calling: GPT-5.5, and tool use: GPT-5.5. Both models share vision, multimodal input, structured outputs, and code execution, 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 (08-06) lists $2.50/1M input and $10/1M output tokens on the cheapest tracked provider, while GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. A 70/30 input-output blend puts GPT-4o (08-06) lower by about $7.75 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 3, so concentration risk also matters.

Choose GPT-4o (08-06) when coding workflow support and lower input-token cost are central to the workload. Choose GPT-5.5 when coding workflow support 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.

FAQ

Which has a larger context window, GPT-4o (08-06) or GPT-5.5?

GPT-5.5 supports 1.05m tokens, while GPT-4o (08-06) supports 128k 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.

Which is cheaper, GPT-4o (08-06) or GPT-5.5?

GPT-4o (08-06) lists $2.50/1M input and $10/1M output tokens on the cheapest tracked provider. GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is GPT-4o (08-06) or GPT-5.5 open source?

GPT-4o (08-06) is listed under Proprietary. GPT-5.5 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 (08-06) or GPT-5.5?

Both GPT-4o (08-06) and GPT-5.5 expose vision. 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 multimodal input, GPT-4o (08-06) or GPT-5.5?

Both GPT-4o (08-06) and GPT-5.5 expose multimodal input. 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-4o (08-06) and GPT-5.5?

GPT-4o (08-06) is available on OpenAI API, Salesforce Einstein Generative AI, and OpenRouter. GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.