HEAD-TO-HEAD · FAST-TIER · VERIFIED SEPTEMBER 30, 2026

Claude Haiku 4.5 vs Grok 4.7: which model costs less for production workloads?

Claude Haiku 4.5 and Grok 4.7 compete in the fast-inference tier with different economics. Haiku 4.5 runs at $1 input and $5 output per million tokens, while Grok 4.7 charges $2 input and $6 output. This comparison shows exactly where each model wins on total cost of ownership.

Spec	Claude Haiku 4.5	Grok 4.7
Input / 1M tokens	$1.00	$2.00
Output / 1M tokens	$5.00	$6.00
Context window	200K	500K

The output price gap

The output pricing gap between Claude Haiku 4.5 and Grok 4.7 is narrower than the input delta. Haiku 4.5 charges $5 per million output tokens versus Grok 4.7's $6—a $1 difference that translates to a 16.7% premium for Grok. On input tokens, the spread widens: Haiku 4.5's $1 rate is exactly half of Grok 4.7's $2, making input-heavy workloads (retrieval, summarization, classification) notably cheaper on Anthropic's model. For typical balanced workloads, the combined effect favors Haiku 4.5 by roughly 25%.

Context window

Claude Haiku 4.5 ships with a 200,000-token context window, suitable for most document-processing and conversational tasks but smaller than Grok 4.7's estimated 500,000-token window. The larger Grok context budget supports multi-document synthesis, longer chat histories, and RAG patterns with extensive retrieved chunks. Neither model enforces a separate output token limit beyond the overall context cap, so developers can allocate context flexibly between prompt and completion depending on workload requirements.

Worked example

At 100 million input tokens and 30 million output tokens per month, Claude Haiku 4.5 costs (100 × $1) + (30 × $5) = $100 + $150 = $250. Grok 4.7 costs (100 × $2) + (30 × $6) = $200 + $180 = $380. The $130 monthly savings with Haiku 4.5 represents a 34% reduction in total spend, assuming no prompt caching or batch discounts. Organizations running input-dominant pipelines see even steeper savings, while output-heavy generation workloads narrow the gap slightly.

Prices from the LLM Price Watch daily tracker, 2026-09-30. Prices change; use the calculator with your own usage for an exact comparison, or see the full price table for every tracked model.

Frequently asked questions

Which model is cheaper overall, Claude Haiku 4.5 or Grok 4.7?

Claude Haiku 4.5 is cheaper across both input and output dimensions. Input tokens cost $1 per million on Haiku versus $2 on Grok 4.7; output tokens run $5 versus $6. For a representative monthly workload of 100M input and 30M output tokens, Haiku 4.5 totals $250 compared to Grok 4.7's $380, a $130 (34%) saving.

Does the context window difference justify Grok 4.7's higher price?

Grok 4.7's estimated 500K context window is 2.5× larger than Haiku 4.5's 200K, which matters for long-document analysis, extensive RAG retrieval, or multi-turn conversations with deep history. If your application requires context beyond 200K tokens, Grok 4.7 may be the only viable option regardless of price. For workloads comfortably under 200K, Haiku 4.5 delivers better value.

How do caching and batch discounts affect the cost comparison?

Both models offer prompt caching (Haiku 4.5 at $0.10/M cache reads, Grok 4.7 likely similar) and batch API pricing that can halve standard rates. Haiku 4.5's batch pricing drops to $0.50 input / $2.50 output per million tokens. If your workload supports asynchronous processing and repeated prompts, caching and batch modes amplify Haiku 4.5's already lower base pricing, widening the cost advantage further.

Which workloads favor Grok 4.7 despite higher per-token costs?

Grok 4.7 excels in scenarios where its larger context window, potential benchmark advantages, or reasoning capabilities offset the price premium. Agentic coding tasks, complex multi-step problem solving, and applications that rely on ingesting entire codebases or long technical documents may justify the extra spend. Benchmark data and qualitative performance testing should guide the decision for intelligence-sensitive use cases beyond pure economics.