Methodology: Batch vs Realtime

When batch processing saves 50% over realtime API.

Citations last refreshed: 2026-10-28 Pricing snapshot: 2026-10-28 ← Back to calculator

How we keep this honest

Every number on aicost.ai is verified by 11 independent audit layers that run every day at 03:30 EDT — covering structural integrity, math correctness, source-side freshness, and cross-source agreement. We publish today's snapshot date and per-vendor verification timestamps below so you can verify any number yourself.

81
calculators
31
vendors verified
62
cited claims
717
days of history
11
audit layers
See the 8 audit layers
  • Layer 1: Architecture (12 structural invariants)
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  • Layer 3: Golden values (math correctness vs reference)
  • Layer 4: Source resilience (independent reference data sources reachable)
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  • Layer 6: Hybrid reconciliation (cross-source agreement)
  • Layer 7: Drift detection (day-over-day price changes)
  • Layer 8: Vendor cache (per-vendor freshness wiring)
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All 8 layers must pass before any pricing data is considered fresh. The infrastructure runs daily and publishes results to an internal dashboard. If any layer flags an issue, it is treated as stop-the-line work.

How this calculator sources its numbers

Every value falls into one of five categories. Numbers without an asterisk are vendor-published, directly observable, or computed by arithmetic on published data. Numbers marked with * are typical best-target values — we state the working range and invite you to override with your own number.

Vendor-published Directly from the vendor's pricing or docs page. No asterisk.
Published benchmark Independent benchmark (e.g. Chatbot Arena, ANN-Benchmarks, vLLM). Cited with date.
Research paper Peer-reviewed or widely-accepted research (e.g. LLMLingua, RAGAS).
Typical target * No single canonical source exists. We state the working range and explain why.
Computed Arithmetic on vendor-published values (e.g. batch discount × standard rate).

Any individual claim may also be tagged with * if its source has not yet been re-verified against the current vendor page — treat such claims as approximate until the next verification cycle resolves them.

Vendor verification freshness

Each vendor's pricing page is independently re-checked on a cadence ranging from daily to weekly. Below: when each relevant vendor was last verified by our automated pipeline.

mistral
2026-10-28
verified today
by auto-pipeline
openai
2026-10-28
verified today
by auto-pipeline
xai
2026-10-28
verified today
by auto-pipeline
google-ai-plans-compare
2026-07-22
verified 98 days ago
by auto-grounded
aws-opensearch
2026-04-26
verified 185 days ago
elastic-cloud
2026-04-26
verified 185 days ago
aws-bedrock-pricing
2026-04-25
verified 186 days ago
azure-openai-pricing
2026-04-25
verified 186 days ago
anthropic-docs
2026-04-17
verified 194 days ago
aws-bedrock-usage-types
2026-04-15
verified 196 days ago
aws-cost-explorer-api
2026-04-15
verified 196 days ago

Vendor-published values

Directly from the vendor's own docs. See per-vendor verification dates in the panel above.

Anthropic Message Batches API usage is charged at 50 percent of the standard API prices.

“All usage is charged at 50 percent of the standard API prices.”
Value
0.500000 fraction of base
Source
Anthropic — Message Batches documentation · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Applies to input tokens, output tokens, and any special tokens for all supported models.

Most Message Batches complete within 1 hour.

“most batches completing within 1 hour”
Value
1.000000 hours
Source
Anthropic — Message Batches documentation · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Batches may take up to 24 hours to process; this is a typical completion time.

Amazon Bedrock offers select foundation models (FMs) from leading AI providers at a 50% lower price for batch inference compared to on-demand inference pricing.

“Amazon Bedrock offers select foundation models (FMs) from leading AI providers like Anthropic, Meta, Mistral AI, and Amazon for batch inference at a 50% lower price compared to on-demand inference pricing.”
Value
0.500000 fraction of base
Source
Amazon Bedrock Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Applies to batch inference for supported models; standard on-demand pricing applies otherwise.

Gemini Batch API provides a 50% cost reduction compared to realtime API pricing.

“check_circleBatch API (50% cost reduction)”
Value
0.500000 fraction of base
Source
Google — Gemini Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Discount applies to input and output token pricing across all models supporting Batch API.

Mistral batch processing reduces the price by 50% compared to real-time inference.

“Batch processing, for high-volume work, reduces the price by 50%”
Value
0.500000 fraction of base
Source
Mistral — Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Applies to all models supporting batch processing; discount is applied to the base per-million-token pricing.

OpenAI Batch API offers a 50% cost discount compared to synchronous APIs.

“Better cost efficiency: 50% cost discount compared to synchronous APIs”
Value
0.500000 fraction of base
Source
OpenAI — Batch API documentation · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Applies to all Batch API endpoints; discount is relative to standard synchronous API pricing.

OpenAI Batch API batches complete within 24 hours.

“Fast completion times: Each batch completes within 24 hours (and often more quickly)”
Value
24.000000 hours
Source
OpenAI — Batch API documentation · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Completion window is fixed at 24 hours; actual completion may be faster.

Gemini 1.5 Flash input tokens are billed at $0.00001875 per 1,000 tokens for <= 128K context and $0.0000375 per 1,000 tokens for > 128K context in realtime mode, and half those rates in batch mode, representing a 50% discount.

“Gemini 1.5 Flash ... Price ( > 128K input tokens) ... $0.0000375 / 1,000 count ... Batch ...”
Value
0.500000 fraction of base
Source
Google — Vertex AI Generative AI Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Discount applies to input tokens only; output tokens also have a 50% batch discount.

Gemini context caching read pricing is $0.10 per 1M tokens through November 30, 2026, and $0.20 per 1M tokens starting December 1, 2026.

“Context caching price | Not available | $0.10 through November 30, 2026.<br>$0.20 starting December 1, 2026.<br>Implicit caching only (explicit caching is not supported).”
Value
0.100000 $/M tokens
Source
Google — Gemini Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Applies to all models with context caching support. Implicit caching only; explicit caching not supported.

Gemini context caching storage pricing is $0.50 per 1,000,000 tokens per hour through December 31, 2026, and $1.00 per 1,000,000 tokens per hour starting January 1, 2027.

“$0.50 / 1,000,000 tokens per hour (storage price) through December 31, 2026.<br>$1.00 / 1,000,000 tokens per hour (storage price) starting January 1, 2027.”
Value
0.500000 $/M tokens/hour
Source
Google — Gemini Pricing · Wed Oct 28 2026 00:00:00 GMT-0400 (Eastern Daylight Time)

Storage fee applies to cached tokens stored per hour. Pricing varies by model tier (e.g., Standard, Batch, Flex, Priority).

Vendor pricing pages referenced

All vendor-published prices used by this calculator are sourced from the pages below. See the verification panel above for when each was last re-checked.

See an error or stale value?

We treat methodology as a living document. If a price is wrong, a benchmark is outdated, or you have a better citation, let us know and we will verify within 48 hours.

Email [email protected] →
AICost.ai pricing data keeps our calculations accurate across top AI and cloud vendors · last updated 2026-10-28

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-10-28.
  • Vendor-published values have no mark. Inferred/extrapolated values are marked with * and listed below.
  • Batch API discounts are 50% off standard rates across providers that offer Batch mode.
  • Prompt caching discounts vary by provider (typically 80-90% off cached input tokens).
  • Regional data-residency surcharges (Anthropic 1.1x, OpenAI 1.1x, Google regional tiers) are NOT included in base rates.
  • Long-context pricing tiers apply when input exceeds model threshold.
  • Embedding prices are input-only (no output tokens generated).

Primary sources

Last-verified date is the most recent successful daily snapshot (aicost_pricing_snapshots) or, when no snapshot exists yet, the latest successful crawler run (aicost_crawler_runs). 10 of 10 vendors are currently verified. Aggregator services (TokenCost, AI Pricing Guru, etc.) are not listed.

Anthropic
2026-10-28
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 714 days captured
Anthropic Docs
2026-10-28
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 714 days captured
OpenAI
2026-10-28
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 715 days captured
Google AI
2026-10-28
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 690 days captured
Google Vertex
2026-10-28
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 690 days captured
DeepSeek
2026-10-28
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 629 days captured
xAI
2026-10-28
https://x.ai/api
Daily snapshot since Nov 2024 · 547 days captured
Mistral
2026-10-28
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 688 days captured
Cohere
2026-10-28
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 714 days captured
Voyage AI
2026-10-28
https://docs.voyageai.com/docs/pricing

Inferred values (marked with * in calculator tables)

Derived from industry conventions, not directly published by the vendor. Typical conventions: cached input = 10% of base (90% off), Batch API = 50% of base (50% off).

Vendor / Model Field Why it’s inferred
Anthropic — Claude Sonnet 4.6 cachedInput Derived at 10% of input rate — Anthropic publishes 90% cache-hit discount on this tier.
Anthropic — Claude Sonnet 4.5 cachedInput Derived at 10% of input rate; same 90% cache-hit convention as Sonnet 4.6.
Anthropic — Claude Sonnet 4.5 batchInput Derived at 50% of standard input — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Sonnet 4.5 batchOutput Derived at 50% of standard output — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Haiku 4.5 cachedInput Derived at 10% of input rate — Anthropic 90% cache-hit discount convention.
OpenAI — GPT-5.4 Mini cachedInput Derived at 10% of input — OpenAI documents automatic 90% discount on cache hits across GPT-5.x tier.
OpenAI — GPT-5.4 Nano cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Nano batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Nano batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Pro batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.2 cachedInput Derived at 10% of input; no residency uplift.
OpenAI — GPT-5.2 batchInput Derived at 50% of input.
OpenAI — GPT-5.2 batchOutput Derived at 50% of output.
OpenAI — GPT-5 cachedInput Derived at 10% of input.
OpenAI — GPT-5 batchInput Derived at 50% of input.
OpenAI — GPT-5 batchOutput Derived at 50% of output.
OpenAI — GPT-5.5 Pro cachedInput Derived at 10% of input — OpenAI does not publish a cached rate for *-pro models; using the family convention.
OpenAI — GPT-5.5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.2 Pro cachedInput Derived at 10% of input — pro-tier convention.
OpenAI — GPT-5.2 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.2 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.1 batchInput Derived at 50% of input.
OpenAI — GPT-5.1 batchOutput Derived at 50% of output.
OpenAI — GPT-5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5 Nano cachedInput Derived at 10% of input.
OpenAI — GPT-5 Nano batchInput Derived at 50% of input.
OpenAI — GPT-5 Nano batchOutput Derived at 50% of output.
Google — Gemini 3 Flash cachedInput Derived at 10% of input — Google caching discount convention ~90%.
Google — Gemini 3.1 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 3.1 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 3.1 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Pro cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.5 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
xAI — Grok 4 (legacy) cachedInput Extrapolated at 25% of base.

Pricing is cross-verified against the LiteLLM community registry when available. Daily snapshots are kept in aicost_pricing_snapshots; every change is logged to aicost_price_changelog with old & new values for full audit trail. Read the full methodology →