The 2026 Coding Leaderboard by Tier
Coding composite indices (0-100), verified 2026-08-28 via OpenRouter's Artificial Analysis feed, with output price and value:
| Tier | Model | Coding | Output $/1M | Coding per $ | Role |
|---|---|---|---|---|---|
| Frontier | Claude Opus 5 | 78.0 | $25.00 | 3.1 | Hard 10%: gnarly refactors, architecture |
| Frontier | GPT-5.6 Sol | 77.4 | $30.00 | 2.6 | Deep reasoning + agentic coding |
| Frontier | Grok 4.6 | 76.8 | $6.00 | 12.8 | Frontier score at balanced price |
| Balanced | GPT-5.6 Terra | 76.7 | $12.00 | 6.4 | Default feature work |
| Balanced | Gemini 3.7 Flash | 76.1 | $6.00 | 12.7 | Fast interactive coding |
| Balanced | GLM 5.3 | 74.8 | $4.40 | 17.0 | Best balanced-tier value |
| Balanced | Claude Sonnet 5 | 71.5 | $10.00 | 7.2 | Reliable all-rounder |
| Budget | GPT-5.6 Luna | 71.4 | $1.20 | 59.5 | Scaffolding, tests, bulk edits |
| Budget | DeepSeek V4 Flash (off-peak) | 56.2 | $0.66 | 85.2 | High-volume code chores |
| Specialist | Codestral 2508 | — | $0.90 | — | FIM completion, inline tools |
Two facts change how you choose. Grok 4.6 is the value outlier of the frontier — Opus-5-tier coding at $6 output, six points better per dollar than Sol. And GPT-5.6 Luna at 71.4 coding is the biggest bargain in the market — 93% of Opus's score at 4.8% of its price.
Session Economics: What Code Work Really Bills
Three realistic sessions, priced at verified 2026-08-28 rates (uncached; caching cuts input ~90% when the prefix repeats):
| Session | Shape | Luna | 3.7 Flash | Sonnet 5 | Opus 5 |
|---|---|---|---|---|---|
| 10-turn code review | 8K ctx/turn, 600 out | $0.023 | $0.156 | $0.220 | $0.550 |
| Feature build (30 turns) | 12K ctx/turn, 900 out | $0.104 | $0.702 | $0.990 | $2.475 |
| Repo refactor (50 turns) | 30K ctx/turn, 1.5K out | $0.390 | $2.700 | $3.750 | $9.375 |
Verify the math on one row — a 50-turn refactor on Gemini 3.7 Flash: input 50×30K×$1.50/1M = $2.25, output 50×1.5K×$6/1M = $0.45 → $2.70. All rows are uncached; caching cuts the input portion ~90% when the prefix repeats, taking a refactor from $2.70 to ~$0.70. The honest weekly range: a week of heavy AI coding bills $10-60 on budget/balanced models and $150-400 on Opus 5 for the same session count.
The 2026 Coding Stack, Tier by Tier
Inline completion & scaffolding → budget + specialists
Codestral, Qwen Coder, Grok Build and GPT-5.6 Luna handle autocomplete, boilerplate and tests. Cheap enough to run hot all day.
Feature work → balanced flagships
Gemini 3.7 Flash for interactive speed, GLM 5.3 or Grok 4.6 for the best value at frontier-adjacent quality, Terra/Sonnet where the team is standardized.
The hard 10% → frontier
Opus 5 or Sol for gnarly refactors, architecture decisions, and anything where a wrong answer costs hours. 25× the output price is cheap insurance on the tasks that deserve it.
Agents that code → agentic index first
Coding score isn't loop performance. For autonomous coding agents, check the agentic axis — GLM 5.3 (59.1) and Sol (57.8) lead the crossover.
Frequently Asked Questions
Which AI model is best for coding in 2026?
By third-party coding composite (verified 2026-08-28): Claude Opus 5 leads at 78.0, then GPT-5.6 Sol (77.4), Grok 4.6 (76.8), GPT-5.6 Terra (76.7), and Gemini 3.7 Flash (76.1) — the top five are within 2 points. Value flips the ranking: GPT-5.6 Luna scores 71.4 at 1/25th of Opus's output price.
What does a coding session actually cost?
A 10-turn code review (8K context, 600 output per turn) costs $0.023 on GPT-5.6 Luna, $0.16 on Gemini 3.7 Flash, $0.22 on Claude Sonnet 5, and $0.55 on Claude Opus 5 — uncached. Caching cuts the input portion ~90% on repeated prefixes, and off-peak DeepSeek makes the same session cheaper still.
Should I use a coding-specialist model or a general flagship?
Specialists (Codestral, Qwen Coder, Grok Build) are cheap and fast but trail the frontier on whole-repo reasoning. The 2026 pattern: budget specialists for scaffolding and inline completion, balanced flagships (Terra/Flash/Sonnet) for feature work, frontier (Opus 5/Sol) only for the hard 10%.
How much does a whole-repo refactor cost?
A 5,000-line refactor at 50 turns with 30K context per turn: about $2.70 uncached on Gemini 3.7 Flash, $3.75 on Claude Sonnet 5, and $9.38 on GPT-5.6 Sol — or $0.39 on GPT-5.6 Luna. With 90% cached input the same refactor drops to roughly a third on models with cheap output.
Does coding benchmark score correlate with real results?
Composite coding indices correlate with agentic coding results but compress the top: the 78 vs 71 gap between Opus 5 and Luna is real but smaller than the 25x price gap. For most repo work, tier placement matters more than rank within a tier.