Grok 4 vs GPT-5
xAI's flagship goes up against OpenAI's flagship in 2026. We compare pricing per million tokens, context window, reasoning, vision, and the cases where each one wins. All numbers verified April 2026.
TL;DR. The Verdict
- Cost per request matters. It's about 40% cheaper at a typical mix.
- You need 400K context and don't want Grok 4.20's overhead.
- You're already on OpenAI SDKs or have prompt caching wired up.
- Output volume is high. GPT-5's $10/M output beats Grok's $15/M.
- You need real-time web data baked in (xAI native search).
- You're building inside the X or xAI ecosystem.
- Output is short and reasoning quality matters more than cost.
- You want a path to 2M context (upgrade to Grok 4.20).
Grok 4 vs GPT-5 at a glance
| Field | Grok 4 (xAI) | GPT-5 (OpenAI) |
|---|---|---|
| Released | Dec 2025 | Sep 2025 |
| Context window | 256K tokens | 400K tokens |
| Input price (per 1M tokens) | $3.00 | $1.25 |
| Output price (per 1M tokens) | $15.00 | $10.00 |
| Cached input | $0.300 | $0.125 |
| Reasoning tier | Excellent | Excellent |
| Speed tier | Fast | Fast |
| Vision support | Yes | Yes |
| Tier | flagship | flagship |
Pricing verified April 2026 against each provider's pricing page. Run the live numbers on our cost calculator.
§1. Pricing: GPT-5 wins on cost across the board
The price gap between the two flagships in 2026 is meaningful. GPT-5 charges $1.25 per million input tokens and $10.00 per million output tokens. Grok 4 charges $3.00 input and $15.00 output. On a typical chat workload of 1,000 input plus 500 output tokens per request, GPT-5 costs $0.00625 per call. Grok 4 costs $0.0105. That's a 68% premium per call for Grok 4, and it compounds quickly at scale.
The gap widens further with prompt caching. OpenAI offers a 90% discount on cached input ($0.125 per million tokens). xAI's cached pricing of $0.300 is also 90% off list, but on a higher base. Run a chatbot with a 5,000-token system prompt (cached) handling 1 million turns per month: GPT-5 cached input alone costs $625, and Grok 4 cached input costs $1,500. Output dominates either way, but at scale that 2.4x multiplier on cache spend is real money.
Where Grok 4 partially closes the gap is on output-light workloads. Single-shot classifications, intent routing, or short summaries all skew the math. If your output averages under 100 tokens per request, the input-cost differential dominates and Grok 4's premium narrows. For most production AI features (chat, content generation, agentic tool use), output is the expensive half and GPT-5 wins comfortably.
§2. Context window: GPT-5 has 56% more, but Grok 4.20 jumps to 2M
GPT-5 ships with 400K tokens of context. Grok 4 has 256K tokens. For 95% of workloads (a single document, a code file, or a normal conversation history) both are more than sufficient. The interesting threshold is when you need to pass a full codebase, a long PDF set, or extended agent traces.
Two practical notes. First, effective recall on every flagship in 2026 starts dropping past roughly 100,000 tokens. People call this the "lost in the middle" problem. Throwing 256K tokens of documents at Grok 4 and 400K at GPT-5 doesn't guarantee both will reason equally well across all of it. RAG against a smaller-context retriever is usually still the right move.
Second, if you genuinely need the largest context available, neither Grok 4 nor GPT-5 is your answer. xAI's Grok 4.20 (2M tokens) and Gemini 2.5 Pro (1M+) lead this niche. Grok 4.20 is also competitively priced at $2.00/$6.00 per million, which makes it the cheapest flagship-tier path to multi-document codebase reasoning in 2026. Worth knowing before locking in on Grok 4.
§3. Reasoning quality: tied at the top
Both Grok 4 and GPT-5 sit at the Excellent reasoning tier in our rubric. In side-by-side tests across coding, analysis, and structured-output tasks, the gap is small enough that choosing on reasoning alone is mostly noise. We've found GPT-5 marginally stronger on structured JSON outputs and tool use. Grok 4 is marginally stronger on open-ended reasoning over recent events (its real-time data integration helps here).
For frontier-tier reasoning, neither is the right pick. OpenAI's o3-pro and o3, Anthropic's Claude Opus 4.7, and OpenAI's GPT-5.5 Pro all sit a tier above on hard reasoning. If you're comparing flagships specifically because reasoning quality is the bottleneck, consider stepping up to one of those instead of choosing between Grok 4 and GPT-5.
§4. Real-time data is Grok's actual differentiator
The single thing Grok 4 does that GPT-5 doesn't is native, low-latency access to current web data through xAI's built-in search. For applications that need to answer "what just happened" or "what's the current state of X" (sports scores, breaking news, market data, recent product releases), Grok 4 returns coherent answers with citations directly from the model.
GPT-5 can match this with the OpenAI Responses API plus the web search tool, but it's a two-call dance with a separate latency hit. If your product's value lives in "current information," Grok 4 is the cleaner integration. If you can tolerate 24-hour staleness, GPT-5 with its cost advantage wins.
§5. How to choose, in 60 seconds
Walk down this list and stop at the first "yes":
- Need real-time web data baked in? Pick Grok 4. xAI's integrated search is the cleanest path.
- Cost is the bottleneck? Pick GPT-5. It's about 40% cheaper at a typical mix, plus deeper prompt-caching savings.
- Need 600K+ context? Neither. Step up to Grok 4.20 (2M) or Gemini 2.5 Pro (1M+).
- Need frontier-grade reasoning? Neither. Step up to GPT-5.5, o3-pro, or Claude Opus 4.7.
- Default for everything else? Pick GPT-5. Bigger SDK ecosystem, better documentation, lower cost, and more battle-tested integrations.
To run actual numbers on your specific workload, plug your token volumes into our LLM cost calculator and compare against 43+ models including GPT-5.5 ($5.00/$30.00), which is the natural upgrade from GPT-5 if you want a step up in reasoning at modest extra cost.
Frequently asked
- Is Grok 4 better than GPT-5 in 2026?
- It depends on what you're building. GPT-5 wins on output cost ($10 per million tokens vs $15) and context window (400K vs 256K). Grok 4 ties on reasoning quality and vision support, and has a notable edge in real-time data access through xAI's built-in web search. For document-heavy or budget-sensitive workloads, pick GPT-5. For agents that need fresh information from the web, Grok 4 is the cleaner choice. If you need very long context, look at Grok 4.20, which jumps to 2 million tokens.
- Which is cheaper, Grok 4 or GPT-5?
- GPT-5 is cheaper across the board. Input runs $1.25 per million tokens versus Grok 4's $3.00. Output runs $10 per million versus $15. GPT-5 also offers a 90% discount on cached input ($0.125), and Grok 4's cached pricing is $0.30. On a typical workload of 1 million input tokens plus 500K output tokens, GPT-5 costs $6.25 and Grok 4 costs $10.50. That puts GPT-5 roughly 40% cheaper at this mix.
- Does Grok 4 have a larger context window than GPT-5?
- No. Grok 4 ships with 256K. GPT-5 ships with 400K. So GPT-5 holds more in a single call. xAI's larger model, Grok 4.20, jumps to 2 million tokens, the biggest mainstream context window of any flagship in 2026. If you genuinely need to reason over a whole codebase or several long documents, Grok 4.20 or Gemini 2.5 Pro (1M+) beat both Grok 4 and GPT-5.
- Does Grok 4 support vision like GPT-5?
- Yes. Both Grok 4 and GPT-5 accept image inputs. One caveat: Grok 4's smaller sibling, Grok 4.1 Fast, is text only. Always check the specific variant before you ship multimodal. Every model in the GPT-5 family (5, 5 Mini, 5 Nano, 5.1, 5.2, 5.5) supports vision.
- Which is faster, Grok 4 or GPT-5?
- Both sit in the Fast tier on our latency rubric. In practice, GPT-5 tends to ship the first token slightly faster on short prompts, while Grok 4 holds steadier throughput on long generations. Real latency depends heavily on prompt length, output length, and provider load, so benchmark with representative inputs before you commit.
- When should I pick Grok 4 over GPT-5?
- Three cases. First, when you need real-time web context: xAI's native search makes Grok 4 the best 'is this fact current' model in 2026. Second, when you're already inside the X or xAI ecosystem and want tight integration. Third, when output volume is small and reasoning quality matters more than per-token cost. For most other production workloads, GPT-5 is the safer default.
- When should I pick GPT-5 over Grok 4?
- Default to GPT-5 when cost, context, and ecosystem maturity matter. GPT-5 is roughly 40% cheaper per typical request, has 56% more context (400K vs 256K), and benefits from OpenAI's much larger SDK and tutorial surface. The OpenAI API also has wider language SDK support than xAI's API. For most teams shipping production AI features in 2026, GPT-5 is the cheaper and faster path to a working integration.