OpenAI vs Anthropic: 2026 comparison

Side-by-side

OpenAI vs Anthropic — at a glance

Dimension	OpenAI	Anthropic
Flagship model	GPT-4o	Claude Sonnet 4.5
Context window	128K	200K
Input price (per 1M tok)	$2.50	$3
Output price (per 1M tok)	$10	$15
Latency (typical)	~450ms TTFT	~600ms TTFT
Free tier	Yes (low quota)	No (paid only)
Best for	Multimodal vision, function calling, structured output, broad ecosystem	Long-context (200K-1M), agentic coding, prompt caching, careful tone

When to choose which

Pick OpenAI or Anthropic?

When to choose OpenAI

Choose OpenAI's GPT-4o when you need a versatile, cost-effective model with the broadest ecosystem support in 2026. GPT-4o is the workhorse for multimodal apps (vision in, structured JSON out), function calling at scale, and shorter user-facing chat where 450ms time-to-first-token matters. The OpenAI SDK is everywhere, fine-tunes are mature, and the platform ships features like Assistants, Realtime audio, and Batch API that Anthropic does not yet match.

Multimodal vision (images, charts, screenshots in a single request)
Best-in-class function calling and JSON schema response_format
Cheaper input/output ($2.50 / $10 per 1M vs $3 / $15)
Largest ecosystem of SDKs, examples, and third-party tools
Lowest TTFT in the flagship tier (~450ms typical)

When to choose Anthropic

Choose Anthropic's Claude Sonnet 4.5 when reliability on long, multi-step tasks matters more than per-token price. Claude leads agentic coding benchmarks (SWE-Bench Verified ~50%) and is famously steerable for careful, on-tone writing. The 200K-token context (and 1M on enterprise tiers), prompt caching, and computer-use API make it the default choice for code agents, contract analysis, and any workload where consistency outweighs latency.

Top score on SWE-Bench Verified and agentic coding tasks
200K context standard, 1M on enterprise (vs 128K for GPT-4o)
Prompt caching cuts repeated-context cost by up to 90%
Strongest at long-form, careful, on-brand writing
Computer-use API for browser/desktop automation

Why not both?

Run OpenAI and Anthropic side-by-side

VerticalAPI lets you switch between GPT-4o and Claude Sonnet 4.5 per-request through a single OpenAI-compatible endpoint. Same SDK, same API key, zero markup on tokens — you pay OpenAI and Anthropic directly with your own keys.

from openai import OpenAI
client = OpenAI(base_url="https://api.verticalapi.com/v1", api_key="vapi_...")

# OpenAI
resp_x = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
    extra_headers={"X-Provider-Key": "sk-..."},
)

# Anthropic — same SDK, same client, different model + key
resp_y = client.chat.completions.create(
    model="claude-sonnet-4-5",
    messages=[{"role": "user", "content": "Hello"}],
    extra_headers={"X-Provider-Key": "..."},
)

Try VerticalAPI free →

VerticalAPI verdict

Use Claude Sonnet 4.5 for agentic coding, long-context analysis (especially with 200K+ documents) and prompt caching. Use GPT-4o when you need multimodal vision, the OpenAI ecosystem (Assistants, fine-tunes, structured output schemas) or the cheapest first-token latency. Through VerticalAPI you can route between both with a single OpenAI-compatible endpoint and BYOK — no SDK migration.

Get started — BYOK both providers →

FAQ

Frequently asked questions

Is GPT-4o or Claude Sonnet 4.5 cheaper per token?

GPT-4o is priced at approximately $2.50 per 1M input tokens and $10 per 1M output tokens. Claude Sonnet 4.5 is approximately $3 per 1M input and $15 per 1M output. On raw list price GPT-4o is about 17% cheaper on input and 33% cheaper on output. Anthropic's prompt caching can cut repeated-context cost by up to roughly 90%, which often closes or reverses the gap on agent workloads that reuse long system prompts.

Which model is better for coding agents?

Claude Sonnet 4.5 leads on SWE-Bench Verified at approximately 50%, versus around 30% for GPT-4o. Anthropic also exposes a computer-use API and prompt caching, which agent frameworks rely on. GPT-4o remains competitive on shorter, function-calling-heavy tasks and benefits from a more mature Assistants API and Realtime audio support.

What is the context window difference?

GPT-4o supports a 128K-token context window. Claude Sonnet 4.5 supports 200K tokens by default, with 1M-token context available on enterprise tiers. For long-document analysis, codebase review, or multi-turn agent runs, Claude has a meaningful headroom advantage. For typical chat and short RAG, 128K is usually enough.

Which has lower latency?

GPT-4o typically shows around 450ms time-to-first-token, versus about 600ms for Claude Sonnet 4.5. For user-facing chat or voice, GPT-4o usually feels snappier. For batch or background agent work, the latency gap matters less than throughput and cost per task.

Can I switch between GPT-4o and Claude through one endpoint?

Yes. VerticalAPI exposes a single OpenAI-compatible endpoint at https://api.verticalapi.com/v1. You send the same request shape and change the model parameter (for example, gpt-4o or claude-sonnet-4-5) and the matching X-Provider-Key header. There is no markup on tokens; you pay OpenAI and Anthropic directly using your own API keys (BYOK).

Caveats

Limitations of this comparison

Public list prices for GPT-4o and Claude Sonnet 4.5 are revised several times per year; numbers here reflect mid-2026 list prices and exclude volume discounts or committed-use deals.
SWE-Bench Verified and other benchmark scores depend on prompt scaffolding and agent framework, so the same model can swing by 5-10 percentage points between published runs.
Latency figures (around 450ms vs 600ms TTFT) are averaged across regions and times of day; actual TTFT depends on prompt length, region, and current provider load.
Prompt-caching savings only apply when a large portion of the prompt is reused across requests; one-off requests see little to no benefit.
This page compares only the flagship pair (GPT-4o and Claude Sonnet 4.5). Smaller tiers such as GPT-4o mini and Claude Haiku 4.5 have very different cost-quality trade-offs.

Outlook

What may change in 12-24 months

Per-token prices for both flagships are expected to keep falling; the absolute price gap between OpenAI and Anthropic may shrink or invert as competition intensifies.
Anthropic is likely to extend the 1M-token context tier to standard pricing, while OpenAI is expected to ship a 1M-context flagship to match.
SWE-Bench Verified scores from both labs will keep climbing, but the meaningful benchmark for buyers will shift from single-shot coding to long-horizon agent tasks measured in success rate per dollar.
Provider lock-in will weaken further as OpenAI-compatible gateways (including VerticalAPI) make swapping models a one-line change rather than an SDK migration.

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