GPT-4o
OpenAI • Multimodal
Context Window128K
Knowledge CutoffUnknown
GPT-4o vs DeepSeek V3
DeepSeek V3 for open-source deployment and cost efficiency, GPT-4o for broad production API coverage.
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DeepSeek V3
DeepSeek • Text
Context Window128K
Knowledge CutoffUnknown
Editorial Verdict
GPT-4o is the premium managed option; DeepSeek V3 is the open, cost-effective alternative.
GPT-4o and DeepSeek V3 are both strong coding models with different deployment profiles. GPT-4o is a premium managed model with mature API; DeepSeek V3 is an open model with strong coding at a fraction of the cost. For API maturity and multimodal, GPT-4o wins. For self-hosted coding with cost constraints, DeepSeek V3 is the better choice.
GPT-4o
- Mature API ecosystem with reliable function calling and JSON mode
- Multimodal capabilities across text, images, audio, and video
- Consistent, reliable code quality across diverse programming languages
Best for: Production applications requiring API maturity, multimodal, and reliable managed service
DeepSeek V3
- Open weights available for self-hosting with full data privacy
- Competitive coding performance at significantly lower API cost
- Strong performance on math and reasoning alongside coding
Best for: Self-hosted or cost-sensitive coding deployments with open model preference
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | GPT-4o | DeepSeek V3 | Winner |
|---|---|---|---|
| Input (per 1M tokens) | Custom | Custom | N/A |
| Output (per 1M tokens) | Custom | Custom | N/A |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | N/A | N/A |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
GPT-4o Total
VariableDeepSeek V3 Total
VariableSavings unavailable (pricing not published for one model).
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
GPT-4oMMLU Signal (Reasoning)DeepSeek V3
69%
69%
GPT-4oHumanEval Signal (Coding)DeepSeek V3
69%
69%
GPT-4oAgentic Tooling SignalDeepSeek V3
69%
69%
GPT-4oMultimodal SignalDeepSeek V3
69%
69%
Capabilities Matrix
Feature highlights for architecture and production fit.
GPT-4o Strengths
- Balanced general-purpose profile for chat, extraction, and automation tasks.
DeepSeek V3 Strengths
- Balanced general-purpose profile for chat, extraction, and automation tasks.
API Implementation
Quick start snippets for each provider style.
OpenAI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai/gpt-4o",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)DeepSeek (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="deepseek/deepseek-v3",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Choose GPT-4o when...
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
Choose DeepSeek V3 when...
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
Frequently Asked Questions
Practical checks before selecting a production model.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
Related Comparisons
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