AgentMeter vs SJolt

AgentMeter and SJolt are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AgentMeter

AgentMeter runs locally — no cloud sync, no account creation, no vendor dashboard to log into — and parses the tool calls, token counts, and caching splits that CLI agents like Claude Code, Gemini CLI, Codex CLI, and Copilot CLI generate. It surfaces the three-tier cost structure that prompt caching creates (input, cached-input, and output tokens each priced differently), which the raw API bill flattens into noise. The value-multiplier calculation compares API spend against estimated developer time saved, giving you a number to put in front of a manager. The wall appears when you need alerting, real-time budget enforcement, or integration with a team billing system — none of that is here.

SJolt

SJolt aggregates generation APIs from ByteDance, Google, and Kuaishou under one request contract, so the same prompt structure, status polling, and result retrieval logic you test in the playground drops directly into production. The catalog spans video (Seedance 2.0, Kling 3.0, Veo 3.1, Gemini Omni), image generation and editing (Seedream V5 Pro, Seedream 4.5), and a depth-map video utility. Cost and usage track against one balance. The wall appears when you need a model not in the catalog — SJolt's coverage is curated, not exhaustive, so teams with niche model requirements will still maintain a second integration.

Attribute	AgentMeter	SJolt
Pricing	Free	Paid
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	macOS, Linux, Windows (Python)	—
Pros	Runs entirely on-device with no account, no cloud sync, and no vendor access to your session data, so usage patterns and project names never leave your machine. Breaks prompt-caching costs into the three actual billing tiers (input, cached-input, output), so you can see whether your caching strategy is paying off instead of inferring it from a flattened total. Per-session and per-project cost aggregation across Claude Code, Gemini CLI, Codex CLI, and Copilot CLI, which means you get a unified spend view instead of hunting across four separate dashboards. Value-multiplier calculation compares API spend against estimated developer time saved, so you have a concrete number when someone asks whether the agent usage is worth the invoice. Open-source under Apache-2.0, so you can audit exactly what it reads and how costs are calculated — no black-box pricing assumptions you have to take on faith.	One API contract covers video and image models from ByteDance, Google, and Kuaishou, so switching models or running A/B comparisons requires no request schema changes — avoiding the per-vendor integration tax that compounds across every new model you evaluate. Playground inputs match production API format exactly, so the test you run to pick a model is the integration you ship — no gap between demo behavior and production behavior. Usage and cost tracking consolidate into a single balance across all model calls, so you see per-model cost comparison without stitching together three vendor dashboards. Depth Video to Video utility converts MP4 source footage into temporally consistent grayscale depth-map video, which gives teams access to a preprocessing step that is otherwise a custom pipeline build. Model output samples are inspectable in-catalog before committing a call, so you validate generation quality against your specific inputs before it touches your production budget.
Cons	There are no budget caps or threshold alerts. A session can exhaust your API credits before AgentMeter reports on it — the tool tells you what happened after the fact, not while it is happening. Teams that need spend enforcement have to wire up separate controls at the API key or infrastructure level. No shared or multi-user view exists. If two developers are both running Claude Code on the same project, their session data stays on their own machines. Teams that need consolidated spend reporting across contributors cannot get it here and will move to a vendor-native dashboard or a shared cost-tracking layer instead. Support is limited to CLI agents (Claude Code, Gemini CLI, Codex CLI, Copilot CLI). If your stack includes API-direct integrations, LangChain pipelines, or custom agent frameworks, AgentMeter produces nothing — you are back to reading raw API logs.	Model coverage is limited to the vendor's curated list — Runway, Stability AI, Pika, and other widely used generation providers are absent. Teams whose target model is outside the catalog ship a direct vendor integration instead, eliminating the aggregator benefit entirely. There is no self-hosted option and no open-source release, so teams with data residency requirements or air-gapped environments cannot use SJolt — they route to direct vendor APIs or on-premise model runners. The platform carries no free tier, per the validator context. Teams evaluating before committing budget must fund a balance top-up to test production-scale call volume, which raises the evaluation cost compared to competitors offering a free usage tier.

Bottom line

AgentMeter is free while SJolt is paid; AgentMeter is open source; only SJolt exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between AgentMeter and SJolt?

AgentMeter is Free and open source, while SJolt is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AgentMeter better than SJolt?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.