DeepSeek vs Phi-3
- ✦ Open source
- ✦ Chain-of-thought reasoning
- ✦ Math solving
- ✦ Edge deployment
- ✦ On-device inference
- ✦ Open-source (MIT)
DeepSeek and Phi-3 are both Large Language Models tools. Compare features, pricing, and ratings below to find the best fit for your team.
When to Choose DeepSeek vs Phi-3
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Chain-of-thought reasoning solves multi-step financial models in spreadsheet via API. Open-source architecture lets compliance teams audit exactly how each answer was reached.
Run on local infrastructure for high-volume APIs. At $0.14/million tokens versus $15 for LLM, startups process millions of queries monthly without vendor lock-in.
Multimodal feature parses documents containing tables and images within internal wiki. Liability clauses and compliance gaps extract with visual context - no separate image-to-text.
Phi-3 Mini quantized to 4-bit runs inference on mobile devices without internet connectivity. Autocomplete and summaries generate 40% faster than API-dependent alternatives.
Fine-tune on proprietary codebases and naming patterns. A fintech backend team cut code review cycles 35% after training on 5,000 examples of internal Go microservices.
Multi-language capability processes user manuals and chatbot queries directly on embedded hardware. No external API calls eliminates bandwidth costs and network latency.
Quantization compresses from 7B to 2B effective size for resource-constrained hardware. A healthcare provider deployed to 200 clinical workstations with only a 2GB footprint each.
Pricing Comparison & PlansHigh· Verified May 30, 2026
DeepSeek Plans
Free tier available
Free
FreeBest for: Get free access to DeepSeek V3 & R1 via web and mobile
- ✓Access to DeepSeek-V3 and DeepSeek-R1 models
- ✓Web interface and mobile app access
- ✓File upload and document analysis
- ✓Web search integration
- ✓Artifacts code preview feature
API Pay-as-you-go
Contact SalesBest for: For custom pricing, contact sales
- ✓DeepSeek-V3: $0.14 per 1M input tokens (cache miss)
- ✓DeepSeek-V3: $0.28 per 1M output tokens
- ✓DeepSeek-R1: $0.55 per 1M input tokens (cache miss)
- ✓DeepSeek-R1: $2.19 per 1M output tokens
- ✓OpenAI-compatible API integration
Phi-3 Plans
Free tier available
Phi-3-mini-4k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00013 per 1,000 tokens
- ✓Output: $0.00052 per 1,000 tokens
- ✓Context length: 4K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3-mini-128k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00013 per 1,000 tokens
- ✓Output: $0.00052 per 1,000 tokens
- ✓Context length: 128K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3.5-mini-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00013 per 1,000 tokens
- ✓Output: $0.00052 per 1,000 tokens
- ✓Context length: 128K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3-small-8k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00015 per 1,000 tokens
- ✓Output: $0.0006 per 1,000 tokens
- ✓Context length: 8K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3-small-128k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00015 per 1,000 tokens
- ✓Output: $0.0006 per 1,000 tokens
- ✓Context length: 128K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3-medium-4k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00017 per 1,000 tokens
- ✓Output: $0.00068 per 1,000 tokens
- ✓Context length: 4K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Phi-3-medium-128k-instruct
Contact SalesBest for: This model requires a custom pricing agreement
- ✓Input: $0.00017 per 1,000 tokens
- ✓Output: $0.00068 per 1,000 tokens
- ✓Context length: 128K tokens
- ✓Pay-As-You-Go offering via Serverless APIs
Open-source. Free to self-host, API pricing via Azure.
Capability Breakdown
14 differences found across 34 standardized features
- •Open source
- •Chain-of-thought reasoning
- •Code generation
- •Math solving
- •Multimodal
- •API access
- •Local deployment
- •Cost-efficient
- •Edge deployment
- •On-device inference
- •Open-source (MIT)
- •128K context
- •Code generation
- •Multi-language
- •Fine-tuning
- •Quantization
- •GGUF support
- •Azure integration
- •Local deployment
- •Low memory footprint
- •Fast inference
- •ONNX support
- •Function calling
- •JSON mode
- •System prompts
- •HuggingFace integration
- •Commercial use
- •No GPU required for small variants
- •REST API
- •Streaming API
- •SDK (Python, JS)
- •Batch Processing
Strengths & Limitations
Evaluative strengths and weaknesses: not feature lists
- +GPT-4 level performance at 98% lower API cost
- +Truly open-source model; fine-tune without restrictions
- +Superior multilingual capabilities, especially in Mandarin
- +Advanced Chain-of-Thought for complex problem-solving
- +Massive 2T token training data for nuanced understanding
- −Documentation and community support are primarily in Mandarin
- −Less mature tooling and integration ecosystem than OpenAI
- −Potential data privacy concerns due to national origin for some users
- −Slower inference speeds on non-specialized hardware
- −Requires more technical expertise to self-host and optimize
- +Runs efficiently on-device, enabling offline AI on phones and IoT
- +MIT license allows for commercial use with minimal restrictions
- +Outperforms larger models on key benchmarks (MMLU, GSM8K)
- +Quantized versions run on CPU, removing expensive GPU requirements
- +Optimized for instruction-following with a high-quality training dataset
- −Limited factual knowledge base compared to models trained on trillions of tokens
- −Struggles with complex, multi-step reasoning and niche topics
- −Not designed for extensive, open-ended conversational chat like larger models
- −Smaller context window (4K/128K) than some frontier models
- −Performance highly dependent on quantization and device hardware
At a Glance
Recent Price History
Phi-3 removed the "Azure AI Serverless API" plan
Plan removed · May 30, 2026
Phi-3 removed the "Open Source (Self-Hosted)" plan
Plan removed · May 30, 2026
Phi-3 added a new "Phi-3-medium-128k-instruct" plan (Custom pricing)
Plan added · May 30, 2026
Phi-3 added a new "Phi-3-medium-4k-instruct" plan (Custom pricing)
Plan added · May 30, 2026
Phi-3 added a new "Phi-3-small-128k-instruct" plan (Custom pricing)
Plan added · May 30, 2026
Plan removed · May 21, 2026
Plan added · May 21, 2026
Frequently Asked Questions
Related Comparisons
Sources & Data Trail · DeepSeek
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-05-21)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4.6/5 · 14 reviews
Sources & Data Trail · Phi-3
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-05-30)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4/5
- 4.Capterra·Capterra verified reviews · 4/5