# AI Pricing Cache (Bedrock + source-provider) **Last updated:** 2026-08-24 **Region:** us-east-1 **Currency:** USD **Accuracy:** ±15-25% for AI models (sourced from public pricing pages) > **Scope: AI/Bedrock only.** This file prices Bedrock model inference and the source-provider > baselines used for migration ROI. It does NOT price infrastructure — azure-to-aws prices > EC2/RDS/S3/ElastiCache/etc. from `references/vendored/pricing/aws-infra-pricing.json` (the > file the `pricing-coverage` gate enforces). Two infra pricing sources would be a drift trap, > so this cache deliberately carries no infra rows. `estimate-ai.md` reads this file for AI > cost; `estimate-infra.md` reads the infra JSON. > > Prices vary by region and change over time; use for estimation only. There is no live pricing > lookup — on a cache miss apply `pricing-fallback.md` (`estimated` or `unavailable`). > **Staleness warning:** if today is more than 30 days after **Last updated**, treat AI model > prices as potentially stale; set `pricing_source: "cached_stale"` in `estimation-ai.json` and > note it. Verify against [aws.amazon.com/bedrock/pricing](https://aws.amazon.com/bedrock/pricing/). --- ## Bedrock Models (On-Demand) **Anthropic Claude (Standard on-demand)** figures match **US East (N. Virginia)** on [Amazon Bedrock pricing](https://aws.amazon.com/bedrock/pricing/) as of cache refresh. **Recommend defaults (new migrations):** Claude Sonnet 5 (flagship), Claude Opus 4.8 (hardest reasoning), Claude Haiku 4.5 (cost/speed). Do not default to Claude Fable 5 (frontier). Long-context SKUs do not all use the same multiplier; confirm batch/cache and cross-region rows per model on that page. See `references/vendored/ai/ai-model-lifecycle.md` for lifecycle detail — **do not recommend Legacy/excluded models for new migrations.** ### Multi-provider quick reference (per 1M tokens) | Model | Model ID | Provider | Input $/1M | Output $/1M | Context | Tier | Status | | ----------------- | ---------------------------------------- | --------- | ---------- | ----------- | ------- | --------- | ---------------------------------------------------------------------------------------------- | | Claude Fable 5 | anthropic.claude-fable-5 | Anthropic | 10.00 | 50.00 | 1M | frontier | active | | Claude Sonnet 5 | anthropic.claude-sonnet-5 | Anthropic | 2.00 | 10.00 | 1M | flagship | active ($2/$10 — launch rate became standard on Sep 1, 2026; the $3/$15 step-up was cancelled) | | Claude Opus 4.8 | anthropic.claude-opus-4-8 | Anthropic | 5.00 | 25.00 | 200K | premium | active | | Claude Sonnet 4.6 | anthropic.claude-sonnet-4-6 | Anthropic | 3.00 | 15.00 | 200K | flagship | active | | Claude Opus 4.6 | anthropic.claude-opus-4-6-v1 | Anthropic | 5.00 | 25.00 | 200K | premium | active | | Claude Haiku 4.5 | anthropic.claude-haiku-4-5-20251001-v1:0 | Anthropic | 1.00 | 5.00 | 200K | fast | active | | Claude Opus 4.1 | anthropic.claude-opus-4-1-20250805-v1:0 | Anthropic | 15.00 | 75.00 | 200K | premium | legacy (EOL Jan 8, 2027) | | Llama 4 Maverick | meta.llama4-maverick-17b-instruct-v1:0 | Meta | 0.24 | 0.97 | 1M | mid | active | | Llama 4 Scout | meta.llama4-scout-17b-instruct-v1:0 | Meta | 0.17 | 0.66 | 10M | efficient | active | | Llama 3.3 70B | meta.llama3-3-70b-instruct-v1:0 | Meta | 0.72 | 0.72 | 128K | mid | active | | Nova 2 Lite | amazon.nova-2-lite-v1:0 | Amazon | 0.33 | 2.75 | 1M | mid | active | | Nova Pro | amazon.nova-pro-v1:0 | Amazon | 0.80 | 3.20 | 300K | mid | active | | Nova Lite | amazon.nova-lite-v1:0 | Amazon | 0.06 | 0.24 | 300K | fast | active | | Nova Micro | amazon.nova-micro-v1:0 | Amazon | 0.035 | 0.14 | 128K | budget | active | | Mistral Large 3 | mistral.mistral-large-3-675b-instruct | Mistral | 0.50 | 1.50 | 256K | flagship | active | | DeepSeek-R1 | deepseek.r1-v1:0 | DeepSeek | 1.35 | 5.40 | 128K | reasoning | active | | gpt-oss-20b | openai.gpt-oss-20b-1:0 | OpenAI | 0.07 | 0.30 | 128K | budget | active | | gpt-oss-120b | openai.gpt-oss-120b-1:0 | OpenAI | 0.15 | 0.60 | 128K | efficient | active | | GPT-5.6 Sol | openai.gpt-5.6-sol | OpenAI | 4.40 | 22.00 | 272K | frontier | active (mantle in-region + runtime CRIS; 1M tier 8.80/33.00) | | GPT-5.6 Terra | openai.gpt-5.6-terra | OpenAI | 2.20 | 13.20 | 272K | flagship | active (mantle in-region + runtime CRIS; 1M tier 4.40/19.80) | | GPT-5.6 Luna | openai.gpt-5.6-luna | OpenAI | 0.22 | 1.32 | 272K | fast | active (mantle in-region + runtime CRIS; 1M tier 0.44/1.98) | | GPT-5.5 | openai.gpt-5.5 | OpenAI | 5.50 | 33.00 | 272K | frontier | active (mantle only; no 1M tier) | | GPT-5.4 | openai.gpt-5.4 | OpenAI | 2.75 | 16.50 | 272K | flagship | active (mantle only; no 1M tier) | _Quick-reference rows use **—** for **model ID** and **context**; resolve in the Bedrock console or AWS model documentation. This is a curated subset for migration selection — see the Bedrock pricing page for the full catalog._ ### Embeddings — Bedrock (per 1M input tokens, US East) Embedding models are **input-only** — priced per 1M input tokens, no output charge. Use for `embedding` capability workloads (RAG corpora, semantic search, FAQ retrieval). A migration from an OpenAI/Azure embedding deployment lands on one of these; note the **dimension** must match (or the corpus must be re-embedded and any similarity threshold recalibrated). | Model | Model ID | Provider | Input $/1M | Dimensions | Tier | Status | | ---------------------------- | ---------------------------- | -------- | ---------- | ----------------- | -------- | ------ | | Titan Text Embeddings v2 | amazon.titan-embed-text-v2:0 | Amazon | 0.02 | 1024/512/256 | default | active | | Titan Text Embeddings v1 | amazon.titan-embed-text-v1 | Amazon | 0.10 | 1536 | legacy | active | | Cohere Embed v4 | cohere.embed-v4:0 | Cohere | 0.12 | 1536/1024/512/256 | flagship | active | | Cohere Embed English v3 | cohere.embed-english-v3 | Cohere | 0.10 | 1024 | mid | active | | Cohere Embed Multilingual v3 | cohere.embed-multilingual-v3 | Cohere | 0.10 | 1024 | mid | active | **Default target for a migrating OpenAI/Azure embedding workload:** Titan Text Embeddings v2 (`amazon.titan-embed-text-v2:0`) — cheapest, configurable dimensions (1024 default; 512/256 for cost/latency). Choose Cohere Embed v4 when the source used a large-dimension model and matrix compatibility or multilingual quality matters. Titan v2 output dimension is configurable, so map `text-embedding-3-large` (3072-dim) or `-small` (1536-dim) to Titan 1024 and **re-embed** — there is no dimension-preserving swap. See `references/vendored/ai/ai-openai-to-bedrock.md`. ### Stability AI — Image Generation (per image, US East) Priced **per image** (not per token). Use for `image_generation` capability workloads. | Model | Model ID | Price/image | Resolution | Tier | Status | | -------------------------- | --------------------------------- | ----------- | ---------- | -------- | ------ | | Stable Image Ultra | stability.stable-image-ultra-v1:0 | $0.08 | up to 4MP | premium | active | | Stable Diffusion 3.5 Large | stability.sd3-5-large-v1:0 | $0.065 | up to 1MP | flagship | active | | Stable Image Core | stability.stable-image-core-v1:0 | $0.04 | up to 1MP | fast | active | > **Cost comparison note:** DALL-E 3 (OpenAI / Azure OpenAI) charges $0.04–$0.12/image by > resolution. When comparing, use per-image cost directly — do not convert Stability AI prices > to per-token equivalents. ### Anthropic Claude — batch & prompt cache (Standard, US East N. Virginia) Per 1M tokens unless noted. | Model | Batch in | Batch out | 5m cache write | 1h cache write | Cache read | | ----------------- | -------- | --------- | -------------- | -------------- | ---------- | | Claude Sonnet 5 | 1.00 | 5.00 | 2.50 | 4.00 | 0.20 | | Claude Opus 4.8 | 2.50 | 12.50 | 6.25 | 10.00 | 0.50 | | Claude Sonnet 4.6 | 1.50 | 7.50 | 3.75 | 6.00 | 0.30 | | Claude Haiku 4.5 | 0.50 | 2.50 | 1.25 | 2.00 | 0.10 | ### OpenAI on Bedrock — the same-model path The proprietary GPT-5.x models on Bedrock are priced at OpenAI's **data-residency tier ≈ 1.10x** the OpenAI standard rates below, and run **`bedrock-mantle` only, in-region only** (no `bedrock-runtime`, no cross-region inference profile for GPT-5.5/5.4). `gpt-oss` DOES support `bedrock-runtime`. For endpoint paths, region matrix, quotas, and prompt-caching detail see `references/shared/openai-on-bedrock.md` (the fact base the mapping guide reads). ## Source Provider Pricing (for Migration Comparison) Use alongside the Bedrock rates to compute migration ROI. This is the **source-side baseline** — what the customer pays today on their current provider. Per `estimate-ai.md`, the authoritative "today" figure is MEASURED/STATED spend (from discovery or clarify); these list rates are the fallback when no measured spend exists, and the source side of the per-model "vs source" column. > **Azure OpenAI uses the OpenAI rows below.** Azure OpenAI serves the same GPT models at list > prices that track OpenAI's, so `ai_source: azure_openai` reads the OpenAI table here — there is > no separate Azure-OpenAI table (plan §19.9a). Azure OpenAI's enterprise/PTU discounts vary per > contract; when the customer's actual spend is known, that overrides these list rates. ### OpenAI / Azure OpenAI (Standard Tier) Prices per 1M tokens. > **Tier note — these are OpenAI STANDARD-tier rates.** Bedrock in-region for the same models is > the OpenAI _data-residency_ tier, exactly 1.10x these figures (see the OpenAI-on-Bedrock note > above). So a same-model move for GPT-5.6 Sol/Terra/Luna, GPT-5.5, GPT-5.4 is a ~10% increase, > not parity — compute the target from the Bedrock table, not by carrying these over. These rows > are the right source-side baseline, and the only figures available for models with **no** > Bedrock equivalent (GPT-5.x Pro, GPT-5.2/5.1, GPT-4.x, o-series). | Model | Input $/1M | Output $/1M | Context | Tier | | ------------- | ------------ | ------------ | ------- | --------- | | GPT-5.6 Sol | _unverified_ | _unverified_ | 1M | frontier | | GPT-5.6 Terra | _unverified_ | _unverified_ | 1M | flagship | | GPT-5.6 Luna | 0.20 | 1.20 | 1M | fast | | GPT-5.5 | 5.00 | 30.00 | 1M | flagship | | GPT-5.5 Pro | 30.00 | 180.00 | 1M | premium | | GPT-5.4 | 2.50 | 15.00 | 1.05M | flagship | | GPT-5.4 Mini | 0.75 | 4.50 | — | fast | | GPT-5.4 Nano | 0.20 | 1.25 | — | budget | | GPT-5.4 Pro | 30.00 | 180.00 | 1.05M | premium | | GPT-5.2 | 1.75 | 14.00 | 200K | flagship | | GPT-5.1 | 1.25 | 10.00 | 200K | flagship | | GPT-5 Mini | 0.25 | 2.00 | 200K | fast | | GPT-5 Nano | 0.05 | 0.40 | 128K | budget | | GPT-4.1 | 2.00 | 8.00 | 1M | flagship | | GPT-4.1 Mini | 0.40 | 1.60 | 1M | fast | | GPT-4.1 Nano | 0.10 | 0.40 | 1M | budget | | GPT-4o | 2.50 | 10.00 | 128K | flagship | | o3 | 2.00 | 8.00 | 200K | reasoning | | o4-mini | 1.10 | 4.40 | 200K | reasoning | > **Azure OpenAI note.** Azure lists the same models under Azure-specific deployment names > (e.g. `gpt-4o`, `gpt-4.1`) and bills per 1M tokens at rates that track the table above. Azure > adds Provisioned Throughput Units (PTU) as an alternative to pay-as-you-go; a customer on PTU > has a committed monthly cost that their stated spend captures directly — prefer stated spend > over these list rates when available. ### Embeddings — OpenAI / Azure OpenAI source (per 1M input tokens) The source-side baseline for a migrating embedding workload. Input-only. Map the "$X today" from measured/stated spend when available; these list rates are the fallback. | Model | Input $/1M | Dimensions | Tier | | ---------------------- | ---------- | ---------- | -------- | | text-embedding-3-large | 0.13 | 3072 | flagship | | text-embedding-3-small | 0.02 | 1536 | fast | | text-embedding-ada-002 | 0.10 | 1536 | legacy | Azure OpenAI bills the same models under deployment names at rates that track this table (PTU caveat above applies). A `text-embedding-3-large` → Titan v2 move is **not** a dimension-preserving swap (3072 → 1024) — it requires re-embedding the corpus and recalibrating similarity thresholds; surface that as a migration task, not a silent cost line. _Gemini source rows from gcp-to-aws are intentionally omitted: azure-to-aws has no `gemini` `ai_source` (plan §19.9b)._