Best LLM caching layer

Combined ranking

1. 1
   RRedis LangCache—10 pts

   GPT #1Claude #1Gemini —

   Purpose-built, fully managed semantic caching with Redis-grade speed, adaptive precision/recall controls, embedding flexibility, TTLs, privacy scoping, and a language-neutral REST API

   To stay #1 Reach general availability with transparent public pricing and broader regional availability

2. 2
   LiteLLM—8 pts

   GPT #4Claude #2Gemini #4

   The de facto open-source LLM gateway ships exact-match and Redis-backed semantic caching across 100+ providers for free, so most teams get response caching as a config flag rather than a new vendor

   To rank higher Harden the semantic-cache layer (per-route similarity thresholds, cache-quality evals, stale-entry invalidation) so it feels engineered rather than bolted on

3. 3
   Portkey—6 pts

   GPT —Claude #3Gemini #3

   AI gateway with both simple and semantic caching plus cost/latency analytics that show cache hit savings directly; easiest path from zero to measurable caching ROI for product teams

   To rank higher More transparent control over embedding choice and similarity scoring so teams can debug false-positive cache hits

4. 4
   GGPTCache—5 pts

   GPT —Claude #5Gemini #2

   A highly modular, open-source library specifically designed for LLM caching, allowing developers to fully customize embedding models, similarity evaluation, and vector storage backends.

   To rank higher Revitalize the open-source maintenance and update dependencies to native support for 2026 agentic frameworks and newer embedding models.

5. 5
   RRedisVL—5 pts

   GPT —Claude —Gemini #1

   High-performance, production-ready semantic caching built directly on Redis vector search, giving developers full control of their caching infrastructure without third-party API dependencies.

   To rank higher Provide an out-of-the-box UI dashboard to monitor cache hits, similarity scores, and logs without requiring custom telemetry setup.

6. 6
   PPortkey AI Gateway—4 pts

   GPT #2Claude —Gemini —

   Simple and semantic caching across hundreds of models, configurable thresholds and namespaces, cache observability, force-refresh controls, and strong gateway features including fallbacks and budgets

   To rank higher Make semantic caching available below its Production and Enterprise tiers

7. 7
   AAzure API Management—3 pts

   GPT #3Claude —Gemini —

   Enterprise-grade semantic-cache policies for Azure and third-party OpenAI-compatible models, tenant partitioning, self-hosted gateways, adjustable similarity thresholds, and deep security and governance integration

   To rank higher Eliminate the operational complexity and extra cost of provisioning an external RediSearch-compatible cache and embeddings backend

8. 8
   Helicone—2 pts

   GPT —Claude #4Gemini —

   One-header caching at the edge with excellent DX, TTL/bucket controls, and observability bundled in, so caching comes with the monitoring you need to trust it

   To rank higher Add true semantic-similarity caching — its exact/bucketed matching leaves most paraphrase-level hit-rate on the table

9. 9
   Cloudflare AI Gatewayincumbent—1 pts

   GPT #5Claude —Gemini —

   Exceptionally easy globally distributed response caching with per-request TTL, bypass and custom-key controls, unified provider support, analytics, rate limiting, and edge delivery

   To rank higher Add general-purpose semantic matching instead of limiting AI Gateway caching to identical requests

10. 10
    UUpstash Semantic Cache—1 pts

    GPT —Claude —Gemini #5

    A fully serverless, zero-ops semantic caching library designed for serverless architectures, integrating seamlessly with Upstash Vector under an affordable pay-as-you-go pricing model.

    To rank higher Offer a robust offline local emulation environment to allow developers to test caching behavior locally without active cloud connections.

By model

Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled continuously