Every "best AI coding agents" or "best AI coding tools" list on the internet ranks tools by vibes. Feature checklists, marketing copy, maybe a screenshot. Here's one ranked by numbers instead: 25 real pull requests, held-out tests, the same judge, measured cost and wall-clock time.

We ran four agentic coding tools (Octomind, Claude Code, Codex CLI and OpenCode) through octobench — 25 tasks taken from real PRs merged in 2026, across Python, PHP, Rust, C++ and JavaScript. Octomind with GLM-5.2 solved 24 of 25. The full data is public in the repo's BENCHMARK.md, and you can run it yourself before you believe a word of this.

One honesty note up front: it's our benchmark, and we're in it. That's exactly why the raw runs are published — every number below is reproducible, and the methodology (task selection, judge model, harness config) is in the repo, pinned to a commit.

#1: Octomind — 24/25 solved, $63.43, 3.6 hours

Best for: long-running, multi-step work where you want the agent to finish, not just start well.

Octomind solved 24 of 25 tasks, scored 2264/2500 with the judge model, and did it for $63.43 in total API spend across the suite. It's a terminal agent built around sessions that persist — you name them, resume them days later, and the full state survives. The same binary runs non-interactively in CI, as a daemon over a WebSocket, or behind ACP for editors.

The trade-off: it's newer than the incumbents, so the ecosystem of guides and Stack Overflow answers is thinner. The docs are good, but you'll be reading them instead of crowdsourcing.

  • Solved 24/25, judge score 2264, $63.43, 3.6h total
  • Multi-provider: GLM-5.2, Claude, GPT, DeepSeek, Gemini — swap mid-session with /model
  • Capabilities load tools on demand, which keeps costs down on big suites
  • Cons: smaller community, you'll read docs more than forum posts

#2: Claude Code — 23/25 solved, $81.79, 6.7 hours

Best for: teams already on Anthropic models who want a polished, opinionated default.

Claude Code solved 23 of 25 and scored 2262 — one task behind, and $18 more expensive across the suite. It's the agent that popularized the terminal-agent category, and the polish shows: good defaults, thoughtful UX, and Anthropic's models behind it.

The constraints are the ones we've written about before — session-based rate limits that bite mid-refactor, auto-compaction you don't control, and single-provider architecture. None of that matters on a Tuesday afternoon. All of it matters on a big task at 11 PM.

  • Solved 23/25, judge score 2262, $81.79, 6.7h total
  • Best-in-class UX and defaults
  • Cons: Anthropic-only, rate limits, sessions expire and compact without asking

#3: Codex CLI — 21/25 solved, $14.86, 1.0 hour

Best for: cost-sensitive batch work and the OpenAI ecosystem.

Codex CLI was the cheapest run by a wide margin — $14.86 for the whole suite, roughly a fifth of Claude Code's bill — and the fastest at one hour wall-clock. It solved 21 of 25. OpenAI's open-source, Rust-built terminal agent with MCP support is the value pick here: if your tasks are well-specified and you're watching spend, it's hard to beat.

The ceiling shows on the harder tasks — the four unsolved ones in our run clustered in the multi-file, cross-language end of the suite.

  • Solved 21/25, $14.86, 1.0h total — cheapest and fastest
  • Open source, MCP support, ChatGPT plan integration
  • Cons: gives up on the hardest multi-step tasks, OpenAI-centric

#4: OpenCode — 19/25 solved, $129.54, 3.3 hours

Best for: terminal-first tinkerers who want an open-source base to modify.

OpenCode is the most-starred open-source agent project on GitHub, and it's a genuinely good harness — same model as our winner (GLM-5.2), so the comparison is apples-to-apples. It solved 19 of 25, but at $129.54 it was the most expensive run of the four, and the gap to Octomind on the same model is a context-management story: what gets loaded, what gets compressed, what the model actually sees per turn.

  • Solved 19/25, $129.54, 3.3h total
  • Open source, huge community, hackable
  • Cons: most expensive per solved task in this run; context handling leaves money on the table

Worth Knowing: Gemini CLI and Aider

Two more we didn't bench in this run, both worth your attention depending on your situation.

Gemini CLI is the free-tier play: 1,000 requests a day and a 1M-token context window on Google's models. If you're experimenting rather than shipping, the price is hard to argue with.

Aider is the git-native one: it works in commits, maps edits to your repo structure, and pairs with almost any model via API keys. If you think in diffs, it thinks like you.

What the Numbers Say That the Listicles Don't

Four things fall out of the data that no feature checklist will tell you.

Cost per solved task varies 9×. Codex at $0.71 per solved task versus OpenCode at $6.82 — same category of tool, wildly different economics.

Model choice matters less than harness efficiency: OpenCode and Octomind ran the same model, and one cost twice as much while solving five fewer tasks.

Time and correctness don't correlate. Codex finished the suite in an hour; the winner took 3.6. Speed tells you about retry strategy, not about whether the work is right.

And "best" is task-shaped. If your work is small, well-specified and cost-sensitive, the cheapest agent wins. If it's long, ambiguous and multi-file, spend the extra $50 on the one that finishes.

Run the benchmark yourself — it's in the repo, pinned and public. Then pick the best AI for coding based on your tasks, not anyone's vibes. Ours included.

Get Octomind — and check BENCHMARK.md before you trust any leaderboard, including this one.

FAQ

What is the best AI for coding in 2026? On our 25-task benchmark of real 2026 PRs, Octomind with GLM-5.2 solved the most tasks (24/25) at $63.43 total spend. Claude Code followed at 23/25. But "best" depends on your tasks: Codex CLI ran at $0.71 per solved task — 5× cheaper than Claude Code — which wins if your work is well-specified. The benchmark is public — run it against your own repos.

Is Claude Code still worth using? Yes — it solved 23/25 in our run, and its UX polish is real. The trade-offs are structural: Anthropic-only models, session rate limits, and auto-compaction you don't control. Teams that hit those walls mid-refactor tend to look for multi-provider alternatives; teams that don't, don't.

What's the cheapest AI coding agent? In this benchmark, Codex CLI at $14.86 for 25 tasks — about $0.71 per solved task, and the clear cost winner on Claude Code vs Codex. Gemini CLI's free tier (1,000 requests/day) is cheaper still if your volume fits inside it. Cheap stops being the right metric when tasks are long and ambiguous; there, per-task completion matters more than per-token price.