LLM Benchmarks
for Developers

Compare AI coding assistants by language and task type. Real performance data: speed, cost, accuracy, and context window. Test Python, TypeScript, Go, Rust, and more. Free and open source.

Benchmark Results

ModelLangTaskContextSpeed (tok/s)Cost ($/1M)Acc (%)Qual (%)
claude-opus-4-6
4.6
PythonCode Gen200K00.0000
claude-opus-4-6
4.6
TypeScriptDebug200K00.0000
claude-sonnet-4-5
4.5
GoCode Gen200K00.0000
claude-sonnet-4-5
4.5
RustRefactor200K00.0000
claude-haiku-4-5
4.5
JavaTest200K00.0000
claude-haiku-4-5
4.5
C#Code Gen200K00.0000
gpt-4o
2024-11
PythonCode Gen128K00.0000
gpt-4o
2024-11
TypeScriptDebug128K00.0000
gpt-4o
2024-11
RubyRefactor128K00.0000
gpt-4-turbo
2024-09
SwiftCode Gen128K00.0000
gpt-4-turbo
2024-09
KotlinTest128K00.0000
gpt-3.5-turbo
0125
PHPCode Gen16K00.0000
llama-3.3-70b
3.3
PythonCode Gen128K00.0000
llama-3.3-70b
3.3
TypeScriptDebug128K00.0000
llama-3.1-405b
3.1
GoCode Gen128K00.0000
llama-3.1-70b
3.1
RustRefactor128K00.0000
deepseek-v3
V3
PythonCode Gen64K00.0000
deepseek-v3
V3
TypeScriptDebug64K00.0000
deepseek-coder-v2
Coder-V2
C++Code Gen64K00.0000
deepseek-v2.5
V2.5
JavaTest64K00.0000
gemini-2.0-flash
2.0
PythonCode Gen1M00.0000
gemini-2.0-flash
2.0
TypeScriptDebug1M00.0000
gemini-1.5-pro
1.5
GoCode Gen2M00.0000
gemini-1.5-flash
1.5
ScalaRefactor1M00.0000
mistral-large
2411
PythonCode Gen128K00.0000
mistral-large
2411
TypeScriptDebug128K00.0000
codestral
2501
RustCode Gen32K00.0000
qwen-2.5-coder
2.5
PythonCode Gen32K00.0000
qwen-2.5-coder
2.5
C#Debug32K00.0000
qwen-2.5
2.5
RCode Gen32K00.0000
kimi-k1.5
K1.5
PythonCode Gen200K00.0000
kimi-k1.5
K1.5
TypeScriptDebug200K00.0000
kimi-k1
K1
JavaCode Gen128K00.0000
Showing 33 results across 13 languages and 4 task types

CLI Tool

terminal

Why Zygur

Stop guessing which LLM to use. Get real data on which models perform best for your actual coding tasks.

Daily Benchmarks

We test Claude, GPT-4, and Gemini every day on real coding tasks. See which model performs best across frontend, backend, database, and DevOps tasks. Fresh data, daily.

Real Code, Real Data

No synthetic benchmarks. We test on actual coding tasks developers face every day. React components, API endpoints, database queries, Docker configs. The stuff you actually build.

Multiple Dimensions

Speed isn't everything. We measure speed, cost, accuracy, and code quality. Because a fast model that writes buggy code isn't actually fast. Get the full picture.

Open Source CLI

Don't trust our tests? Run your own. Our CLI tool is free and open source. Test with your own prompts, your own tasks, your own standards. Full transparency.

Built by Vibe Coders

We're not CS PhDs. We're developers who learned to code with AI. We test what matters to us, and developers like us. Practical benchmarks, not academic exercises.

No BS Methodology

Our testing methodology is public. See exactly how we score models, what prompts we use, and how we measure quality. No hidden criteria, no bias, just data.

CLI Tools for AI Developers

Stack-specific benchmarks (React ≠ Go ≠ Python). Free tool shows which models win for YOUR languages. Paid router uses them automatically.

llm-bench

Stack-Specific LLM Benchmarks

In Development

Free, open source CLI tool testing Claude, GPT-4, Gemini, DeepSeek, Llama, Qwen, and top models. By language. By framework. We test React separately from Go separately from Python. Because you don't code in 'general'.

Free & Open Source
60+ Test Cases7 Categories30+ StacksLatest Models OnlyOpen Source Included
npm install -g llm-bench

llm-router

Stack-Aware Model Routing for Code

Planned

Routes React prompts to Claude (87 score), Go prompts to GPT-4 (90 score), Python to DeepSeek (88 score). Optimize for speed, cost, or quality with one parameter. Backed by stack-specific benchmark data. CODE ONLY - not chat, not images, just code.

$49/month + API costs
Stack-Specific RoutingSpeed/Cost/Quality ModesCommercial + Open SourceCode-Focused
Coming Q2 2026

Why We'll Win

1. Stack-specific testing. Every other benchmark tests "coding" as one thing. We test React, Go, Python, Rust, and 20+ stacks separately. Because you don't code in "general" - you code in specific languages.

2. Fully open source. Most benchmark platforms are closed black boxes. Ours isn't. Verify methodology, run your own tests, contribute improvements. Trust through transparency.

llm-bench launching February 2026. llm-router launching Q2 2026. Building in public at @zygurdev.

Building in Public

Follow along as we ship daily LLM benchmarks and build CLI tools for AI developers. Built by a vibe coder, for vibe coders.