o3 for coding
o3 is ranked #8 on LLMDex's llm for coding ranking out of 8 models we track for this use case. Below, the specific reasons it slots where it does, and when you should reach for an alternative.
Updated
At a glance
- Rank
- #8 of 8
- Context
- 200K tokens
- Output / 1M
- $8.00 / 1M tokens
- Released
- Apr 2025
Why o3 fits this task
Three things about o3 that map directly onto what this task rewards: Industry-leading reasoning depth at launch; Strong on math, science, and abstract puzzles; Tool-use during reasoning loops. Beyond the task-specific fit, o3 also brings industry-leading reasoning depth at launch and strong on math, science, and abstract puzzles, both of which compound when the workload broadens.
The criteria this task rewards
LLMDex ranks best llm for coding on 5 criteria , these are the axes the ranking uses, in priority order:
- SWE-bench Verified score on real repository tasks
- HumanEval / LiveCodeBench function-level accuracy
- Long-context handling for multi-file edits (≥128k tokens)
- Tool-use and function-calling reliability for editor agents
- Output cost per million tokens, coding agents burn output fast
How o3 scores on each axis
Where o3 costs you: slow first-token, unpredictable total latency. For most teams this is acceptable on this workload, the value of the strengths above outweighs the cost. For cost-bound workloads or teams with strict latency budgets, run an eval against the next two ranked models on real data before committing.
Strengths that pay off here
- Industry-leading reasoning depth at launch
- Strong on math, science, and abstract puzzles
- Tool-use during reasoning loops
Tracked weaknesses
- Slow first-token, unpredictable total latency
- Expensive when reasoning runs long
When to pick something else
If you can pay slightly more or accept slightly different tradeoffs, Qwen2.5-Coder-32B from Alibaba ranks one position higher and tends to win on the hardest cases. Open-weight code specialist, frequently the top open option for self-hosted code completion.
Run o3 now
Skip setup. Deploy via a hosted provider in under a minute.
Other models for coding
- Claude Opus 4.7 for coding
Anthropic's mid-2026 flagship, ahead on SWE-bench, agent reliability, and writing quality.
Read guide - GPT-5.5 for coding
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Read guide - Claude Sonnet 4.6 for coding
Anthropic's mid-tier 4.6 release, the workhorse model behind most production Anthropic deployments.
Read guide - Gemini 3 Pro for coding
Google's late-2025 flagship, set new benchmarks on long-context, vision, and reasoning at competitive pricing.
Read guide - DeepSeek-V3 for coding
DeepSeek's flagship 671B-parameter MoE, frontier-level quality at a tiny fraction of frontier prices.
Read guide
o3 for other use cases
Direct comparisons
Frequently asked
Is o3 good for coding?
o3 is ranked #8 on LLMDex's coding list. OpenAI's flagship reasoning model, set the bar for hard math, GPQA, and agent benchmarks in 2025.How much does o3 cost for coding?
o3 costs $2.00 / 1M tokens for input tokens and $8.00 / 1M tokens for output tokens. For coding workloads, output costs typically dominate; budget on the higher number.What's a cheaper alternative to o3 for coding?
Look at the full Best LLM for Coding ranking for cheaper picks at lower ranks.When should I NOT use o3 for coding?
Tracked weakness: Slow first-token, unpredictable total latency. If that constraint is binding for your workload, the next-ranked model on this task is the safer pick.
Intelligence, distilled weekly.
One short email every Friday, new model launches, leaderboard moves, and pricing drops. Curated by hand. Free, no spam.