GPT-5.5 vs Grok 4.3

Side-by-side pricing, context windows, and capabilities, plus a verdict on which one to pick.

Quick verdict

Grok 4.3 is dramatically cheaper: $1.25/$2.50 against GPT-5.5's $5/$30, a 12x difference on output. Look at one number before deciding: Grok caps output at 30K tokens per response while GPT-5.5 goes to 128K, and Grok doesn't take PDF input. Our honest read: Grok 4.3 is the aggressive-value pick for high-volume text workloads with modest per-response length; GPT-5.5 remains the safer bet for long-form generation and paid tool-calling work.

GPT-5.5 Grok 4.3
Provider OpenAI xAI
Input price $5/Mtok $1.25/Mtok
Output price $30/Mtok $2.5/Mtok
Context window 1,050,000 1,000,000
Max output tokens 128,000 30,000
Input modalities text, image, pdf text, image, pdf
Capabilities vision, tools, reasoning, structured output vision, tools, reasoning, structured output
Released 2026-04-23 2026-04-17

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Why is Grok so much cheaper?

xAI is pricing to win volume. Grok 4.3 lists at $1.25/Mtok input and $2.50/Mtok output; GPT-5.5 lists at $5 and $30. On output tokens that's a 12x difference, one of the largest gaps between models that plausibly compete at the same tier.

The monthly math is stark. A workload of 1M input and 200K output tokens per day costs about $330/month on GPT-5.5 and about $52/month on Grok 4.3. At that ratio you can run Grok experimentally on full production traffic for less than a sixth of what GPT-5.5 costs, which is exactly what we'd suggest doing before believing anyone's benchmark claims, including ours.

Where does the 30K output cap bite?

Grok 4.3's output tops out at 30K tokens per response; GPT-5.5 allows 128K. For chat, classification, extraction, summarization, and most agent substeps, 30K is plenty; responses in those workloads rarely clear a few thousand tokens.

It bites on single-shot long-form generation: full reports, large code files, document drafting in one pass. If that's a core workload, the cap is disqualifying, not inconvenient. Chunking a 100K-token artifact into four 25K responses is possible but adds stitching logic and failure modes you didn't have before.

There's a second input-side gap: GPT-5.5 reads PDFs natively; Grok takes text and images only. Document-heavy pipelines need a text-extraction stage in front of Grok.

Is Grok's quality actually competitive?

Both models are reasoning models with 1M-class context and tool calling, and on everyday text tasks Grok 4.3 holds its own. The honest caveat is maturity: OpenAI's tool-calling behavior, SDKs, eval ecosystem, and operational track record are more battle-tested than xAI's. For a paid product where a malformed tool call is a customer-visible bug, that maturity is worth real money. For internal tooling, batch processing, and cost-sensitive features, it's worth much less than 12x.

Which should you run?

Pick GPT-5.5 if:

  • Single responses regularly need to be very long
  • You ingest PDFs directly
  • Tool-calling reliability is customer-facing

Pick Grok 4.3 if:

  • Your responses stay comfortably under 30K tokens
  • Volume makes 12x-cheaper output decisive
  • You can absorb the occasional rough edge of a younger ecosystem

At these prices, the experiment costs almost nothing: mirror a slice of production traffic to Grok, diff the outputs, and let your own data make the call.

Frequently Asked Questions

How much cheaper is Grok 4.3 than GPT-5.5?

Grok 4.3 costs $1.25/Mtok input and $2.50/Mtok output against GPT-5.5's $5/$30, which is 4x cheaper on input and 12x on output. A 1M-input, 200K-output daily workload runs about $52/month on Grok against $330/month on GPT-5.5.

What is Grok 4.3's output token limit?

30K tokens per response, against 128K for GPT-5.5. That is ample for chat, extraction, and agent substeps, but restrictive for single-shot generation of large documents or files.

Can Grok 4.3 read PDFs?

No. Grok 4.3 accepts text and image input. GPT-5.5 additionally accepts PDFs natively, so document-heavy pipelines on Grok need a separate text-extraction step.

Is Grok 4.3 good enough for production?

For high-volume text workloads with modest response lengths, yes, and the price makes trialing it nearly free. For customer-facing tool calling and long-form generation, GPT-5.5's more mature ecosystem and 128K output ceiling make it the safer choice.

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Spec data last synced August 28, 2026 from models.dev. Pricing can change; confirm on the provider's page before committing.