Pricing Comparison: OpenAI vs xAI pricing: a comparison for AI product builders

OpenAI segments its lineup into premium, mid, and value tiers. xAI ships one flagship at a time and prices it under OpenAI's. Grok 4.5 launched July 8, 2026 at less than a quarter of gpt-5.6-sol's monthly cost on the standardized workload below, a gap worth understanding before comparing AI token pricing line by line.

OpenAI vs xAI at a glance

Takeaway: xAI undercuts OpenAI's flagship more than 4x on the standard workload but offers no budget tier for high-volume small tasks.

Model overview

OpenAI's current lineup is the gpt-5.6 family, launched July 9, 2026. gpt-5.6-sol is the flagship at $5 / $30, gpt-5.6-terra the mid tier at $2.50 / $15, and gpt-5.6-luna the value pick within the family at $1 / $6. The gpt-5.5 and gpt-5.4 generations stay on the card, with gpt-5.5-pro as the premium reasoning option and gpt-5.4-nano as the cheapest model at $0.20 / $1.25.

xAI sells one current model. Grok 4.5 launched July 8, 2026 at $2 / $6 with 500k context and cached input at $0.50. There is no small-model tier, the flagship is the whole API lineup. On the consumer side, SuperGrok runs $30/mo and SuperGrok Heavy $300/mo.

Key features

Pricing snapshot

Prices verified July 13, 2026. Providers reprice often, see the update timeline below.

OpenAI API pricing

Standard tier, per 1M tokens, prompts up to 200k. Long-context rates where noted.

Batch API: roughly 50% off. Cached input: 10x cheaper than base input. Web search tool: $10 per 1k calls.

xAI API pricing

Per 1M tokens.

Consumer plans: SuperGrok at $30/mo, SuperGrok Heavy at $300/mo.

Chat plans

What this costs at a real workload

The standardized scenario: 1,000 requests per day at roughly 1,000 input and 1,000 output tokens each, which works out to about 30M input and 30M output tokens per month. Monthly cost = 30 x input rate + 30 x output rate.

Tokenizer caveat for the Claude rows: Fable 5, Sonnet 5, and Opus 4.7+ use a new tokenizer that produces roughly 30% more tokens for the same text. Comparing per-token rates across providers understates Anthropic's effective cost per request by about that margin. Rate cards don't tell you what the invoice will say. The tokenizer does.

Grok 4.5 at $240 per month sits close to gpt-5.6-luna at $210, while delivering flagship positioning against gpt-5.6-sol at $1,050. The catch is at the bottom: there is no xAI answer to gpt-5.4-nano for classification-style volume.

The spread across all six providers is 143x between the most and least expensive model for the same workload. The full 15-row table is on the AI Pricing Index. For how per-token rates turn into unit economics, see token economics.

Timeline of past updates

OpenAI

• July 9, 2026: gpt-5.6 family launch. Sol at $5 / $30, terra at $2.50 / $15, luna at $1 / $6

• April 24, 2026: gpt-5.5 launch at $5 / $30, doubling flagship input over gpt-5.4

• April 9, 2026: ChatGPT Pro $100 tier added below the $200 tier

• April 2, 2026: Team plan renamed Business, $25/user/mo

• March 5, 2026: gpt-5.4 family launch at $2.50 / $15, doubling over gpt-5

• August 2025: GPT-5 launch at $1.25 / $10

Trajectory: Flagship input went $1.25 to $2.50 to $5.00 in under a year. 4x.

xAI

• July 8, 2026: Grok 4.5 at $2 / $6, up from Grok 4.3's $1.25 / $2.50, well under OpenAI and Anthropic flagships

• May 15, 2026: model retirement wave

• March 10, 2026: Grok 4.20 API release at $2 / $6, following the earlier grok-4.1 pricing revision

• September 2025: grok-4-fast at $0.20 / $0.50

• July 2025: Grok 4 launch at $3 / $15

Trajectory: Mixed, trending aggressive on price-performance.

The AI Pricing Index

OpenAI logged 6 price events in 12 months, flagship input up 4x. xAI logged 5, mixed in direction: Grok 4.5 raised the flagship rate 60% over Grok 4.3, while grok-4-fast pushed the floor down in 2025. xAI's pattern is aggressive price-performance resets rather than steady drift, which makes each event bigger when it lands.

The index counts documented list-price events per provider over the trailing 12 months, recounted monthly. Full methodology and all six provider timelines are on the AI Pricing Index.

What this means for your own pricing

If you build on OpenAI, xAI, or both, this pricing complexity becomes your pricing complexity. Four problems show up regardless of which side you pick.

• The margin problem. Every user interaction has variable cost. A power user generating long responses on a flagship model costs 10-50x more than a casual user on a value model. Per-seat pricing doesn't see this. You need usage-aware billing to protect margins.

• The model mix problem. Products route different requests to different models, and the table above shows the cost range that creates inside a single product. Your billing system needs to know which model served which request and price accordingly.

• The credit translation problem. Many AI products abstract provider costs with credit-based pricing. That means maintaining a conversion layer from usage to credits to dollars. Every provider price event forces you to re-derive the conversion rates.

• The visibility problem. Finance needs margin by customer, by feature, by model, by month. If your metering system lives apart from your billing system, that reconciliation happens in spreadsheets.

The index above adds the repricing angle: these two providers logged 11 price events in 12 months between them. Each one forces you to re-derive your own margins, credit conversion rates, and FX exposure. Solvimon runs that layer: metering per provider, credits and wallets as first-class primitives, rate cards you update without an engineering sprint. See Solvimon for AI.

Related

• OpenAI vs Gemini pricing. OpenAI and Google token prices, plans, and repricing records.

• OpenAI vs Anthropic pricing. Two flagships priced within dollars, and a tokenizer that changes the math.