Take back control of your coding-AI bill.

Run GLM 5.2 on AMD Hardware with Featherless AI. Starting at $7.5K/mo.

Reserve a node

Same coding workload. A fraction of the cost.

Dedicated vs. per-token

Size dedicated GLM 5.2 capacity and compare against per-token pricing.

What's the main model you are paying for today? *

Max context window

Size your workload — enter any one

Number of developers

Total tokens / month

tok/mo

Current monthly spend

$ /mo

Enter developers, tokens, or spend to size your capacity.

Enter your workload to size dedicated capacity.

Assumes ~20K input / 600 output per request; cache hit 80% dedicated, 70% serverless. List prices from public rate cards. Featherless does not guarantee any particular cost savings. Contact to run detailed benchmark or run a poc on your workloads.

Talk to an engineer

Reserve a dedicated coding node.

Tell us your team size, number of devs, and what you’re spending today. We’ll size the node, confirm pricing, and hand you a drop-in endpoint.

✓ Flat, forecastable monthly cost

✓ Claude- & OpenAI-compatible — switch in minutes

✓ A guarantee against token bill shock

Want your developers to vet quality first? Choose “a POC on our repo” in the form and we’ll prove it on your codebase.

GLM 5.2 codes at the frontier.

BenchmarksHugging Face

Official GLM-5.2 coding benchmarks.

View the model card →

GLM-5.2 long-horizon coding benchmarks vs Opus 4.8 and GPT-5.5

LeaderboardArena

GLM 5.2 ranks #2 on the Arena WebDev coding leaderboard

See the leaderboard →

#ModelScore

1claude-fable-51653

2glm-5.2 (max)1584

3claude-opus-4-8-thinking1561

4claude-opus-4-7-thinking1559

5claude-sonnet-5-thinking1551

Code Arena · WebDev · Jul 2026 · 422k votes

AnalysisMedium

“GLM 5.2 beats Claude Fable 5 : GLM 5.2 Benchmarks explained.”

Read the analysis →

GLM 5.2
> Fable 5

Developer by day. Agent by night.

Daytime · developer-first

Your engineers, unthrottled

Prioritize interactive work when people are online.

IDE coding assistants
Pull-request reviews
Code generation
Inline completions

developers 75%agents 25%

After hours · agent-first

Agents that never clock out

Maximize the node when developers are offline.

Autonomous coding agents
Repository-scale analysis
Refactoring & migrations
Test & bug discovery

developers 10%agents 90%

What’s included

One dedicated endpoint for coding assistants, autonomous agents, and repo-scale automation across your whole org.

✓ Claude-compatible API endpoints

✓ OpenAI-compatible API endpoints

✓ Optimized for your codebase and workloads

✓ GLM 5.2-powered inference

✓ Multi-model routing

✓ Up to 1M context window

✓ Autonomous agent workloads

✓ Maximum caching to reduce cost

✓ Dedicated capacity allocation

FAQ

Frequently asked questions

What's the cheapest way to run coding agents at scale?

A dedicated node at a flat monthly price. Per token APIs charge for every token, and agents generate huge volume — so your bill grows with each agent you add. A Featherless Dedicated Coding Node runs GLM 5.2 on AMD MI325 for one fixed cost: add agents for free until the node is full. In our internal scenario that's about ~$12K/mo flat vs. ~$41K metered. Note: figures are illustrative pending our published benchmark.

Is GLM 5.2 good enough for coding vs. Claude Opus or GPT 5.5?

Our team and our customers say yes. For the read edit test loop coding agents actually run, GLM 5.2 holds its own against frontier models — and the cost difference closes any small gap. Best answer: prove it on your own repo. We'll run a POC on your codebase so your team judges quality before you spend a dollar.

What's a cheaper alternative to OpenRouter, GitHub Copilot, or Claude Code?

A Featherless Dedicated Coding Node. It's a drop in for the same tools — Claude and OpenAI compatible — but swaps per token and per seat metering for a flat monthly cost.

Can I use GLM 5.2 with Claude Code, Cursor, and other coding agents?

Yes. The endpoint is Claude and OpenAI compatible, so it works with Claude Code, Cursor, Cline, Continue, Aider, the OpenAI and Anthropic SDKs, and your own agents. Most teams switch by changing the base URL and API key — no migration project.

How much does it cost to run coding agents 24/7?

Starts at ~$7.5K/mo, based on an estimated 1B output tokens per month and over 100B total tokens per month. It's a flat price, so running agents around the clock doesn't change the bill.

Why does Featherless use AMD MI325 instead of NVIDIA?

Three reasons. We have supply. We have proprietary optimization for GLM 5.2 on AMD. And compared with 8xH100s, it lowers the entry price from $20K per month to $7.5K, making it far more accessible.

Is my source code kept private?

Yes. A dedicated node is reserved and isolated for your organization — not shared infrastructure — so your code, prompts, and context stay inside your trust boundary. We support specific compliance and data residency needs on request.

What context window does it support?

A half node supports up to a 256K token context window — enough for repository scale agent sessions. A full node supports up to 1M. Our customers rarely need larger context; it's occasional. The industry average is around 20K input tokens.

Who is Featherless Dedicated Coding Nodes for?

Any engineering team spending more than roughly $7.5K/month on coding AI — about ~10 developers at an AI native company or ~60 at a larger org. If your per token or per seat bill keeps climbing and you run coding agents at scale, the economics work.