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Posted on • Originally published at remoteopenclaw.com

Best OpenAI Models for OpenClaw — GPT-4o, o1, o3 Ranked

#claude #ai #productivity #tutorial

Originally published on Remote OpenClaw.

The best OpenAI model for most OpenClaw operators right now is o3, because it delivers strong reasoning at $2/$8 per million tokens with a 200K context window — making it 7.5x cheaper than o1 on input while handling agentic workflows reliably. If budget matters more than peak reasoning, GPT-4.1 at $2/$8 per million tokens with a 1M context window is the strongest general-purpose alternative.

Key Takeaways

  • o3 is the best reasoning model for OpenClaw at $2/$8 per million tokens with 200K context and 100K max output.
  • GPT-4.1 offers the largest context window (1M tokens) at $2/$8 per million tokens — strong for long agent sessions.
  • o4-mini at $1.10/$4.40 per million tokens is the cheapest reasoning option that still handles tool calling well.
  • GPT-4o-mini at $0.15/$0.60 per million tokens is the budget workhorse for lightweight OpenClaw tasks.
  • Reasoning models (o3, o4-mini) consume hidden reasoning tokens billed as output — set max_completion_tokens to control costs.

Part of The Complete Guide to OpenClaw — the full reference covering setup, security, memory, and operations.

In this guide

  1. Which OpenAI Model Should You Use with OpenClaw?
  2. Model Comparison Table
  3. OpenAI API Key Setup for OpenClaw
  4. Model-by-Model Breakdown
  5. Cost Optimization Tips
  6. Limitations and Tradeoffs
  7. FAQ

Which OpenAI Model Should You Use with OpenClaw?

OpenAI currently offers six models that matter for OpenClaw operators, split across two families: the GPT series (general-purpose) and the o-series (reasoning-focused). As of April 2026, the OpenAI API pricing page shows a wide range from $0.15 to $15 per million input tokens, so the right pick depends entirely on your workload.

For most OpenClaw use cases — tool calling, multi-step workflows, persona interactions — reasoning models like o3 outperform raw GPT models because OpenClaw's agent loop benefits from structured chain-of-thought. But if your tasks are mostly simple retrieval, summarization, or short exchanges, GPT-4.1 or GPT-4o-mini will save you significant cost without sacrificing quality.

The key decision is whether you need reasoning depth (o-series) or raw throughput at lower cost (GPT series). For operators running OpenClaw as an always-on agent, that distinction drives most of your monthly spend.

Model Comparison Table

As of April 2026, these are the OpenAI models most relevant to OpenClaw operators, ranked by cost-effectiveness for agent workloads. Pricing is per million tokens from the OpenAI API pricing docs.

Model

Input / Output (per 1M tokens)

Context Window

Max Output

Best For

o3

$2.00 / $8.00

200K

100K

Reasoning-heavy agent tasks, complex tool chains

GPT-4.1

$2.00 / $8.00

1M

32K

Long-context agent sessions, codebase analysis

o4-mini

$1.10 / $4.40

200K

100K

Budget reasoning with tool calling

GPT-4o

$2.50 / $10.00

128K

16K

Multimodal tasks, image understanding

GPT-4.1-mini

$0.40 / $1.60

1M

32K

High-volume agent work at low cost

GPT-4o-mini

$0.15 / $0.60

128K

16K

Lightweight tasks, triage, classification

o1

$15.00 / $60.00

200K

100K

Maximum reasoning (rarely justified for OpenClaw)

OpenAI API Key Setup for OpenClaw

OpenClaw connects to OpenAI through your API key stored in the configuration file at ~/.openclaw/openclaw.json. The OpenAI API keys page is where you generate the key, and you need an active billing account before the key will work.

Step-by-step setup:

  1. Go to platform.openai.com/api-keys and create a new secret key.
  2. Copy the key immediately — OpenAI only shows it once.
  3. Add it to your OpenClaw configuration: 
{
  "providers": {
    "openai": {
      "apiKey": "sk-your-key-here",
      "baseUrl": "https://api.openai.com/v1",
      "models": ["o3", "gpt-4.1", "o4-mini", "gpt-4o-mini"]
    }
  }
}
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Do not commit your API key to version control. Use environment variables or add openclaw.json to your .gitignore. For a full walkthrough, see the OpenClaw API key guide.

Model-by-Model Breakdown

o3 — Best Overall for OpenClaw Reasoning Workflows

OpenAI's o3 costs $2 per million input tokens and $8 per million output tokens with a 200K context window and 100K max output tokens. It is 7.5x cheaper on input than o1 while delivering comparable reasoning quality for most agent tasks.

Choose o3 when:

  • your OpenClaw workflows involve multi-step tool calling,
  • you need the model to reason through complex instructions before acting,
  • you want the strongest cost-to-reasoning ratio in the OpenAI lineup.

One critical detail: o3 uses internal reasoning tokens that are billed as output tokens. A simple-looking response can consume 5-10x more tokens than the visible output. Set max_completion_tokens in your requests to prevent runaway costs.

GPT-4.1 — Best for Long-Context Agent Sessions

GPT-4.1 matches o3's pricing at $2/$8 per million tokens but ships with a 1M token context window — the largest in OpenAI's current lineup. That makes it the strongest pick when your OpenClaw sessions involve large codebases, long document chains, or extended multi-turn conversations.

GPT-4.1 does not have the o-series reasoning loop, so it will not outperform o3 on tasks that require deep chain-of-thought. But for straightforward agent work where context length matters more than reasoning depth, it is often the better choice.

o4-mini — Best Budget Reasoning Model

At $1.10/$4.40 per million tokens, o4-mini is 13.6x cheaper on input than o1 and still handles tool calling and structured reasoning. It shares the same 200K context window and 100K max output as o3.

Use it when you want reasoning capabilities but your tasks are not complex enough to justify o3's slightly higher cost. For many routine OpenClaw agent loops — calendar management, email triage, simple research — o4-mini delivers enough reasoning quality at roughly half the price of o3.

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GPT-4.1-mini — Best High-Volume Workhorse

GPT-4.1-mini costs $0.40/$1.60 per million tokens with the same 1M context window as GPT-4.1. According to OpenAI, it matches or exceeds GPT-4o on most intelligence evaluations while reducing latency by nearly half and cutting cost by 83%.

This is the model to use when you are running OpenClaw at high volume — many concurrent sessions, lightweight tasks, or triage operations — and you want to keep monthly spend low without dropping to the smallest models.

GPT-4o-mini — Cheapest Viable Option

At $0.15/$0.60 per million tokens, GPT-4o-mini is the lowest-cost OpenAI model that still delivers useful results for OpenClaw. It supports a 128K context window and 16K max output. Use it for simple classification, quick lookups, and tasks where reasoning depth does not matter.

o1 — Premium Reasoning (Rarely Needed)

o1 costs $15/$60 per million tokens. It was the first reasoning model in OpenAI's lineup, and o3 has since replaced it for most practical purposes at a fraction of the cost. The only reason to use o1 is if you have a very specific workflow where it measurably outperforms o3 — and for most OpenClaw operators, that situation does not come up.

Cost Optimization Tips

OpenAI API costs can add up fast with an always-on agent like OpenClaw. These strategies reduce spend without degrading quality.

  • Use model routing. Configure OpenClaw to use GPT-4o-mini for simple tasks and o3 only when reasoning is needed. The cost difference between the two is more than 13x on input.
  • Set max_completion_tokens. Reasoning models use hidden tokens. Capping output prevents a single complex query from burning through your budget.
  • Use cached input pricing. OpenAI offers 50% off cached inputs — $1.25 instead of $2.50 per million tokens on GPT-4o. Structure your prompts so the system message stays stable across requests.
  • Use the Batch API. If your OpenClaw tasks can tolerate async processing, the Batch API gives you 50% off both input and output costs.
  • Monitor per-session cost. Track token usage per OpenClaw session to identify which workflows consume the most tokens, then optimize or downgrade those specific flows.

For a deeper breakdown, read the OpenClaw API cost optimization guide.

Limitations and Tradeoffs

OpenAI models through the API have real constraints that matter for OpenClaw operators.

  • Reasoning token costs are unpredictable. o3 and o4-mini use internal reasoning tokens that are invisible but billed as output. A task that looks cheap can spike to 10x the expected cost. Always set max_completion_tokens.
  • No local option. Unlike Ollama models, OpenAI models require an internet connection and API access. If your OpenClaw setup needs to run fully offline, OpenAI is not an option.
  • Rate limits matter. High-volume OpenClaw deployments can hit rate limits, especially on reasoning models. Check your tier on the OpenAI dashboard and request increases before scaling.
  • GPT-4o is being superseded. GPT-4.1 is cheaper and has a larger context window. If you are still defaulting to GPT-4o, consider switching to GPT-4.1 for the same price tier with better specs.
  • Context window does not equal quality. A 1M token context window on GPT-4.1 does not mean the model reasons equally well across all million tokens. For very long sessions, test whether quality degrades in practice.

Related Guides

FAQ

What is the best OpenAI model for OpenClaw in 2026?

The best overall model is o3 at $2/$8 per million tokens. It offers strong reasoning for agent workflows at a fraction of o1's cost. For long-context work, GPT-4.1 matches the price with a 1M token context window.

How much does it cost to run OpenClaw with OpenAI models?

Monthly cost depends on usage volume. A light operator using GPT-4o-mini at $0.15/$0.60 per million tokens might spend under $5/month. Heavy reasoning workloads on o3 at $2/$8 per million tokens can run $30-100/month depending on session length and frequency.

Should I use o3 or GPT-4.1 for OpenClaw?

Use o3 when your OpenClaw tasks require multi-step reasoning, complex tool calling, or structured problem-solving. Use GPT-4.1 when you need the largest possible context window for long documents or extended agent sessions without heavy reasoning demands.

How do I set up an OpenAI API key for OpenClaw?

Generate a key at platform.openai.com/api-keys, then add it to your OpenClaw config at ~/.openclaw/openclaw.json under the providers section. Make sure billing is active on your OpenAI account or the key will not work.

Is GPT-4o still worth using with OpenClaw?

GPT-4o at $2.50/$10 per million tokens is being overtaken by GPT-4.1 at $2/$8 with a larger context window. Unless you specifically need GPT-4o's multimodal image capabilities, GPT-4.1 is the better choice for most OpenClaw workflows as of April 2026.

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