Anthropic Claude vs OpenAI GPT vs DeepSeek — API comparison for developers

The query "buy an AI API" lumps together three completely different model families: Claude from Anthropic, GPT from OpenAI, and DeepSeek from China. All three solve similar problems — text generation, code, reasoning, RAG, agents. But they have different strengths, different prices, and different availability depending on where you are.

We'll break down what to pick for which task in 2026, and how to pay for each one through LiteAI.

Quick model overview

	Anthropic Claude	OpenAI GPT	DeepSeek
Flagship	Claude Opus 4.8	GPT-5 (upcoming)	DeepSeek V3.2 / R1
Strongest suit	Reasoning, long context, code	Versatility, ecosystem, speed	Price, reasoning (R1)
Context	up to 1M (Opus-1m)	up to 128K–400K	up to 128K
Open source	No	No	Yes (V3, R1)
Tool use	Yes	Yes	Yes
Multimodal	Vision, PDF	Vision, Audio, Realtime	Text

Anthropic Claude

What it's best at:

• Long reasoning: Opus 4.8 is the strongest model for tasks that require keeping a large context in mind: codebase refactoring, legal document analysis, multi-step agents.
• Code: Sonnet 4.6 is the main model for programming in Claude Code, Cursor and Cline. Code quality competes with GPT-5, sometimes exceeds it.
• Long context: Opus with the 1M context is a unique advantage — no other model offers this.
• Accuracy: Claude fabricates facts less often and is better at refusing when it's unsure.

Weak spots:

• Multimodality isn't at OpenAI's level (Vision is there, Audio/Realtime aren't).
• A bit slower than Haiku competitors on simple tasks.
• Pricier than DeepSeek (but cheaper than top-tier GPT).

Price (through LiteAI):

• $1 per 1M tokens — one flat rate for Opus / Sonnet / Haiku.

OpenAI GPT

What it's best at:

• Versatility: GPT has been the "default" pick for a long time. It performs well across a broad range of tasks without fine-tuning.
• Ecosystem: Assistants API, Realtime API, DALL-E, TTS, Whisper — all on one platform. If you need the full stack (text + images + voice), pick GPT.
• Tool use and Structured Outputs: OpenAI has historically had the best function calling and JSON mode support.
• Speed: GPT-4o mini, GPT-5 (when it ships) are among the fastest on the market.

Weak spots:

• Shorter context (128K vs 1M on Opus).
• Pricier than DeepSeek for large volumes.
• A reputation for "hallucinating more" compared to Claude (though the gap shrinks with each version).

Price (through LiteAI and similar):

• GPT-4o: ~$2 per 1M tokens (input+output averaged).
• GPT-4o mini: ~$0.20 per 1M tokens — the cheapest "decent" model.

DeepSeek

What it's best at:

• Price: DeepSeek V3 is 10–20× cheaper than top-tier models. For mass tasks (classification, summarisation, chatbots) — the default pick.
• R1 (reasoning): DeepSeek-R1 is a reasoning model competing with OpenAI o1 and Claude Opus. Strong in math, logic, and step-by-step reasoning.
• Open source: can be run locally on your own GPUs.
• High-volume chatbots: 10,000+ requests per day — where Claude and GPT get expensive, DeepSeek stays cheap.

Weak spots:

• Code quality and complex reasoning are below Claude Opus and GPT-5.
• DeepSeek's servers aren't always stable for Western IPs — providers like LiteAI or OpenRouter are needed.
• Weak multimodality.
• 128K context (same as GPT).

Price:

• DeepSeek V3 — from $0.07 per 1M tokens.
• R1 — from $0.27 per 1M tokens.

What to use when

Backend for your own SaaS

If you're building a RAG support bot or a document summariser, DeepSeek V3 or GPT-4o mini is usually enough. They're 10–20× cheaper than top-tier models, and the quality for routine tasks is comparable. Claude Opus is overkill here.

Agentic programming (Claude Code, Cursor Composer)

Claude Sonnet 4.6 is the best pick. The model is tuned for code work: it understands project context, follows instructions, refactors large chunks.

DeepSeek V3 is an alternative for experiments, but Sonnet is more stable. GPT-4o is comparable in quality but more expensive.

Analytical tasks: legal documents, contracts, reports

Claude Opus 4.8 is unrivaled thanks to the 1M context. You can fit an entire document folder in one request and get a coherent analysis. With GPT you'd have to split into chunks and stitch them, which is lower quality.

Reasoning: math, logic, multi-step chains

DeepSeek R1 is a strong contender. On benchmarks like MATH it often beats GPT and approaches Claude Opus. At 5× the price difference in your favour.

Voice assistants, realtime

OpenAI is the only option with a Realtime API. Anthropic and DeepSeek don't have that mode.

Image generation

OpenAI DALL-E is the standard. Claude and DeepSeek don't offer it.

Local self-host (your own GPUs)

DeepSeek is the only one with open-source releases you can run locally. V3 is fine for inference on H100, R1 for reasoning. Claude and GPT are proprietary — self-hosting isn't possible.

Price comparison (LiteAI, end of 2026)

Model	Price per 1M tokens	What you get
Claude Opus 4.8	$1	Top reasoning quality, 1M context
Claude Sonnet 4.6	$1	Balance of speed and quality for code
Claude Haiku 4.5	$1	Fastest, for mass tasks
GPT-4o	~$2	Versatility, ecosystem
GPT-4o mini	~$0.20	Cheap workhorse
DeepSeek V3	~$0.07	Cheapest for basic tasks
DeepSeek R1	~$0.27	Reasoning at an accessible price

Example calculation for a backend service running 5M tokens per day:

Model	Daily spend	Monthly
Claude Opus	5M × $1 = $5	$150
GPT-4o	5M × $2 = $10	$300
DeepSeek V3	5M × $0.07 = $0.33	$10

For mass tasks the difference is 30×.

Strategy: use multiple models

In production you usually use several models for different tasks:

1. DeepSeek V3 / GPT-4o mini — main flow: classification, summarisation, chat. Cheap, fast, good enough for 80% of requests.
2. Claude Sonnet 4.6 — code and programming, agent tasks. More expensive, but better.
3. Claude Opus 4.8 — for hard cases: 1M context, fine-grained analysis. A router decides which request goes to which model.

Routing is implemented through the LiteAI OpenAI-compatible endpoint (https://api.liteai.tech/v1), where you plug the model you want into the model field:

import openai

client = openai.OpenAI(
    api_key="sk-bf-...",
    base_url="https://api.liteai.tech/v1"
)

def route_request(prompt: str, complexity: str) -> str:
    model = {
        "low": "deepseek-chat",
        "medium": "claude-sonnet-4-6",
        "high": "claude-opus-4-8",
    }[complexity]

    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
        max_tokens=1024,
    )
    return response.choices[0].message.content

That same sk-bf-… key works for Claude, GPT, and DeepSeek — one account, one payment, different models.

Bottom line

• Claude — the top pick for code, long context and agent tasks. You pay a bit more and get the quality.
• GPT — the universal soldier with the broadest ecosystem. Voice, images, Realtime.
• DeepSeek — the cheapest alternative for mass tasks, especially reasoning through R1.

Through LiteAI all three families are available via a single key, paid in USDT, with no VPN. That's a rare advantage — usually each ecosystem needs its own account with its own payment.

If you have one backend and need to pick — start with DeepSeek V3 (cheap baseline), add Claude Sonnet for code, and keep Claude Opus in reserve for those 5% of requests that need above-average quality.