Grok 3 vs Grok 4: xAI's model naming explained

xAI’s model naming follows a straightforward integer progression, but the Grok 3 vs Grok 4 naming discussion matters because each generation has introduced meaningful capability shifts rather than incremental bumps. Grok 3 launched in February 2025 with significant reasoning improvements and a new “Think” mode. Grok 4 remains unannounced as of this writing, but xAI’s release cadence and public statements give us a reasonable basis for what to expect. This breakdown covers what’s confirmed, what’s probable, and how to plan around both.

XAI’s naming philosophy

xAI uses a simple major-version scheme: Grok-1 (November 2023), Grok-1.5 (March 2024), Grok-2 (August 2024), Grok-3 (February 2025). No “Turbo,” “Pro,” “Ultra,” or date suffixes. Each major version has corresponded to a new base model trained with substantially more compute. Minor versions (.5) have been checkpoint releases with targeted improvements — longer context, better coding, reduced hallucination — without retraining from scratch.

This matters for capacity planning. When you see “Grok-3” in an API response or provider dashboard, you’re talking to a specific model artifact trained in late 2024. There’s no ambiguity about which variant you’re hitting, unlike some providers where “gpt-4o” might route to one of several checkpoints depending on the day.

Grok 3: what shipped

Grok 3 arrived with three notable capabilities that distinguish it from Grok-2:

Reasoning mode (“Think”) — A dedicated inference-time compute budget that lets the model work through multi-step problems before answering. This isn’t a separate model; it’s the same weights with a different sampling configuration. Latency increases 3-10x depending on problem complexity, but accuracy on math, coding, and logic benchmarks improves measurably.

128k context window — Up from 8k in Grok-2 and 128k in Grok-1.5. The full window is available in both standard and Think modes.

Improved tool use — Native function calling with stricter schema adherence. Grok-2’s function calling was functional but prone to hallucinated parameters; Grok-3’s is production-ready for structured extraction workflows.

Pricing through xAI’s API (the only first-party source) sits at $3/million input tokens and $15/million output tokens for standard mode. Think mode bills at the same per-token rate but consumes more output tokens per request. There’s no separate “reasoning token” surcharge.

{
  "model": "grok-3",
  "messages": [{"role": "user", "content": "Debug this recursion..."}],
  "reasoning_effort": "high",
  "max_tokens": 8192
}

The reasoning_effort parameter accepts low, medium, high, or none (default). none disables Think mode entirely and returns the fastest response.

Grok 4: what’s probable

xAI has not announced Grok 4. No release date, no benchmarks, no API spec. But three signals point to a late 2025 or early 2026 launch:

1. Compute scaling — xAI’s Colossus cluster (100k H100s, expanding to 200k) came online mid-2024. Training a GPT-4-class model takes 3-6 months on that scale. The timeline aligns.

2. Public statements — Elon Musk has referenced “Grok 4” in interviews as the next major training run, targeting “PhD-level” reasoning on STEM tasks. Treat this as directional, not a commitment.

3. Competitive pressure — OpenAI’s o1 series, Anthropic’s Claude 4 series (expected), and Google’s Gemini 2.5 thinking models all ship in 2025. xAI cannot afford a 12-month gap.

Reasonable expectations for Grok 4 based on this pattern:

• Native reasoning — Think mode becomes the default behavior, not a toggle. The model emits reasoning traces by default, with an option to suppress for latency-sensitive paths.
• Multimodal parity — Grok-2 added image understanding; Grok 3 kept it. Grok 4 will likely add native image generation and possibly video understanding, matching Gemini and GPT-4o capabilities.
• Longer context — 256k or 1M tokens, following the industry trajectory.
• Distilled variants — A “Grok-4-mini” or “Grok-4-fast” for cost-sensitive workloads, similar to how Grok-1.5 served as a cheaper Grok-1 alternative.

Pricing will almost certainly increase. Every frontier model generation has commanded a premium. Budget 2-3x Grok-3 rates for initial access.

Head-to-head comparison

Integration ergonomics

Grok 3’s API is OpenAI-compatible with two xAI-specific extensions: reasoning_effort and search_parameters (for the built-in web search tool). The client SDKs (Python, TypeScript, Go) are thin wrappers around the REST endpoint — no surprises.

from xai import XAI

client = XAI(api_key=os.getenv("XAI_API_KEY"))

# Standard call
resp = client.chat.completions.create(
    model="grok-3",
    messages=[{"role": "user", "content": "Summarize this PR"}],
    max_tokens=2048
)

# Reasoning call
resp = client.chat.completions.create(
    model="grok-3",
    messages=[{"role": "user", "content": "Design a lock-free queue"}],
    reasoning_effort="high",
    max_tokens=8192
)

If you’re routing through a gateway (like n4n.ai), the model identifier stays grok-3 and the extensions pass through unchanged. The gateway honors reasoning_effort and forwards provider cache-control headers, so you get deterministic routing without vendor lock-in.

Grok 4 will almost certainly keep the same OpenAI-compatible surface. xAI has shown zero interest in fragmenting their API. The migration cost will be updating the model string and testing for behavior changes in your prompts — standard major-version hygiene.

Ecosystem and limits

Rate limits — xAI’s public API tiers: 60 RPM / 150k TPM on the free tier, 500 RPM / 2M TPM on paid. Enterprise contracts negotiate higher. These are per-organization, not per-model, so Grok-3 and Grok-4 will share quota.

Data retention — Zero retention on API requests by default. Opt-in logging for debugging. No training on API data. This matches Anthropic and exceeds OpenAI’s default (which retains for 30 days unless you opt out via enterprise agreement).

Regional availability — Single global endpoint (api.x.ai). No regional deployments yet. Latency from Europe/Asia adds 100-200ms. If you need data residency, you’ll need a proxy layer or wait for xAI to announce regions.

Model deprecation policy — xAI has not published a formal lifecycle. Grok-1 and Grok-1.5 remain accessible. Grok-2 is still served. Assume 12-month minimum support after a successor launches, but pin your model version explicitly in production:

# Good: explicit version
model="grok-3-20250215"  # if xAI adopts dated snapshots

# Risky: floating alias
model="grok-3"

Which to choose

Choose Grok 3 today if:

• You need reasoning now — Think mode works well for coding agents, multi-step analysis, and math-heavy workflows. The opt-in design lets you control latency per request.
• Cost predictability matters — Known pricing, stable API, no migration risk.
• You’re building on xAI’s search tool — The integrated web search (via search_parameters) is genuinely useful for research assistants and beats maintaining your own RAG for current events.
• Your traffic fits within current rate limits — 2M TPM handles substantial production workloads.

Wait for Grok 4 if:

• You need native multimodal generation — Image output, video understanding, or unified vision-language-action workflows. Grok 3 cannot generate images.
• Reasoning must be default — If your product UX assumes every response includes a reasoning trace (like o1-style interfaces), Grok 3’s opt-in model adds friction.
• Context >128k is a hard requirement — Long-document analysis, full-repo coding agents, or multi-hour conversation histories.
• You can absorb a 2-3x cost increase — Budget for frontier-model pricing. If your unit economics break at $30/M output tokens, Grok 4 isn’t for you yet.

Hedge with a gateway if:

• You want fallback to Claude 4 / GPT-5 / Gemini 2.5 — When (not if) Grok 4 launches with issues or rate limits, automatic fallback keeps your product live.
• You need per-token metering across providers — Unified usage dashboards beat stitching together four vendor consoles.
• You want to test Grok 4 against alternatives on day one — Swap the model string in your routing config, compare latency/quality/cost, promote the winner.

The Grok 3 vs Grok 4 naming question resolves to a simple timeline decision. Grok 3 is a capable, well-priced reasoning model available today. Grok 4 will be a more capable, more expensive model available in 6-12 months. If your roadmap can absorb a model swap in Q4 2025, build on Grok 3 now and plan the migration. If you need capabilities Grok 3 doesn’t have (image generation, 1M context, default reasoning), design for Grok 4’s API shape but don’t block ship on it.