DeepSeek R1 vs Kimi K2 (Groq): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for DeepSeek R1 (DeepSeek) and Kimi K2 (Groq) (Groq). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Mar 6, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: DeepSeek R1 at $4.90/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestDeepSeek R1 | DeepSeek | $4.90 | $0.000490 | $2.80 | $2.10 | 80.4% | Alerts coming soon |
Kimi K2 (Groq) | Groq | $25.00 | $0.002500 | $10.00 | $15.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | DeepSeek R1 | Kimi K2 (Groq) | Cheaper |
|---|---|---|---|
| Input (standard) | $0.28/M | $1.00/M | DeepSeek R1 |
| Output | $0.42/M | $3.00/M | DeepSeek R1 |
| Cached input | $0.03/M | N/A | — |
Prices last verified: 2026-03-06
Cost Breakdown by Usage Volume
Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.
| Volume | DeepSeek R1Monthly | Kimi K2 (Groq)Monthly | DeepSeek R1Per request | Kimi K2 (Groq)Per request |
|---|---|---|---|---|
| 1K requests/mo | $0.49 | $2.50 | $0.000490 | $0.002500 |
| 10K requests/mo | $4.90 | $25.00 | $0.000490 | $0.002500 |
| 100K requests/mo | $49.00 | $250.00 | $0.000490 | $0.002500 |
| 1M requests/mo | $490.00 | $2,500.00 | $0.000490 | $0.002500 |
Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.
Price History
Input price per 1M tokensWhen to Choose DeepSeek R1
by DeepSeek
- Code generation
- Document summarization
Input / 1M tokens
$0.28/M
Output / 1M tokens
$0.42/M
Context window
128,000
Tier
reasoning
When to Choose Kimi K2 (Groq)
by Groq
- Code generation
- RAG / Semantic search
Input / 1M tokens
$1.00/M
Output / 1M tokens
$3.00/M
Context window
256,000
Tier
premium
Key Differences Beyond Price
Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.
| Capability | DeepSeek R1 | Kimi K2 (Groq) |
|---|---|---|
| Context window | 128,000 tokens | 256,000 tokens |
| Max output tokens | 64,000 tokens | 32,768 tokens |
| Performance tier | Reasoning | Premium |
| Vision / image input | No | No |
| Function calling | No | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | Yes | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 30 |
DeepSeek R1 notes
V3.2 unified pricing. Open-source weights available. Off-peak discounts available.
Kimi K2 (Groq) notes
Moonshot AI's flagship model on Groq hardware.
Frequently Asked Questions
Is DeepSeek R1 cheaper than Kimi K2 (Groq)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), DeepSeek R1 costs $49.00/month versus $250.00/month for Kimi K2 (Groq) — a 80% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.
Which model has a larger context window, DeepSeek R1 or Kimi K2 (Groq)?
Kimi K2 (Groq) has a larger context window at 256,000 tokens, compared to 128,000 tokens for DeepSeek R1. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do DeepSeek R1 and Kimi K2 (Groq) support the Batch API?
Neither DeepSeek R1 nor Kimi K2 (Groq) currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.
Which model offers better prompt caching?
DeepSeek R1 supports prompt caching at $0.03/M for cached input, while Kimi K2 (Groq) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, DeepSeek R1's caching capability can substantially reduce effective costs.
What are the best use cases for DeepSeek R1 vs Kimi K2 (Groq)?
Both models are well-suited for Code generation. DeepSeek R1 is particularly strong for Document summarization. Kimi K2 (Groq) is favored for RAG / Semantic search. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.
What is the cost per request for DeepSeek R1 vs Kimi K2 (Groq)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — DeepSeek R1 costs $0.000490 per request and Kimi K2 (Groq) costs $0.002500 per request. At 100,000 requests/month, that translates to $49.00 and $250.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
DeepSeek R1 vs Kimi K2 (Groq): Summary
When comparing DeepSeek R1 and Kimi K2 (Groq) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. DeepSeek R1 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $49.00/month, compared to $250.00/month for Kimi K2 (Groq).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. DeepSeek R1 charges $0.28/M for input tokens and $0.42/M for output tokens. Kimi K2 (Groq) charges $1.00/M input and $3.00/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.
Prompt caching is supported by DeepSeek R1 but not Kimi K2 (Groq). For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.
Context window capacity differs between the two: Kimi K2 (Groq) supports up to 256,000 tokens in a single request, versus 128,000 tokens for DeepSeek R1. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.
Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.
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Relevant Use Cases
See cost recommendations for workloads where DeepSeek R1 or Kimi K2 (Groq) is recommended.