LLM ReferenceLLM Reference

GPT-5.5 vs Grok 4.20 Multi-Agent

GPT-5.5 (2026) and Grok 4.20 Multi-Agent (2026) are frontier-tier reasoning models from OpenAI and xAI. GPT-5.5 ships a 1.1M-token context window, while Grok 4.20 Multi-Agent ships a 2M-token context window. On pricing, Grok 4.20 Multi-Agent costs $1.25/1M input tokens versus $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 4.20 Multi-Agent is ~300% cheaper at $1.25/1M; pay for GPT-5.5 only for coding workflow support.

Decision scorecard

Local evidence first
SignalGPT-5.5Grok 4.20 Multi-Agent
Decision fitCoding, RAG, and AgentsRAG, Agents, and Long context
Context window1.1M2M
Cheapest output$30/1M tokens$2.5/1M tokens
Provider routes2 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.5 when...
  • GPT-5.5 uniquely exposes Vision, Multimodal, and Code execution in local model data.
  • Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
Choose Grok 4.20 Multi-Agent when...
  • Grok 4.20 Multi-Agent has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Grok 4.20 Multi-Agent has the lower cheapest tracked output price at $2.5/1M tokens.
  • Local decision data tags Grok 4.20 Multi-Agent for RAG, Agents, and Long context.

Monthly cost at traffic

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

Lower estimate Grok 4.20 Multi-Agent

GPT-5.5

$11,500

Cheapest tracked route: OpenAI API

Grok 4.20 Multi-Agent

$1,625

Cheapest tracked route: xAI Console

Estimated monthly gap: $9,875. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.5 -> Grok 4.20 Multi-Agent
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Grok 4.20 Multi-Agent is $27.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
Grok 4.20 Multi-Agent -> GPT-5.5
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-5.5 is $27.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • GPT-5.5 adds Vision, Multimodal, and Code execution in local capability data.

Specs

Specification
Released2026-04-232026-01-01
Context window1.1M2M
Parameters
Architecturedecoder only-
LicenseProprietaryProprietary
Knowledge cutoff2025-12-

Pricing and availability

Pricing attributeGPT-5.5Grok 4.20 Multi-Agent
Input price$5/1M tokens$1.25/1M tokens
Output price$30/1M tokens$2.5/1M tokens
Providers

Capabilities

CapabilityGPT-5.5Grok 4.20 Multi-Agent
VisionYesNo
MultimodalYesNo
ReasoningYesYes
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 vision: GPT-5.5, multimodal input: GPT-5.5, and code execution: GPT-5.5. Both models share reasoning mode, 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.

For cost, GPT-5.5 lists $5/1M input and $30/1M output tokens, while Grok 4.20 Multi-Agent lists $1.25/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Grok 4.20 Multi-Agent lower by about $10.88 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.

Choose GPT-5.5 when coding workflow support are central to the workload. Choose Grok 4.20 Multi-Agent when long-context analysis, 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-5.5 or Grok 4.20 Multi-Agent?

Grok 4.20 Multi-Agent supports 2M tokens, while GPT-5.5 supports 1.1M 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-5.5 or Grok 4.20 Multi-Agent?

Grok 4.20 Multi-Agent is cheaper on tracked token pricing. GPT-5.5 costs $5/1M input and $30/1M output tokens. Grok 4.20 Multi-Agent costs $1.25/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.5 or Grok 4.20 Multi-Agent open source?

GPT-5.5 is listed under Proprietary. Grok 4.20 Multi-Agent 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-5.5 or Grok 4.20 Multi-Agent?

GPT-5.5 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-5.5 or Grok 4.20 Multi-Agent?

GPT-5.5 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-5.5 and Grok 4.20 Multi-Agent?

GPT-5.5 is available on OpenAI API and OpenRouter. Grok 4.20 Multi-Agent is available on OpenRouter and xAI Console. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.