GPT-4.1 vs Kimi K2 (Groq): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT-4.1 (OpenAI) 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 8, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Kimi K2 (Groq) at $25.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestKimi K2 (Groq) | Groq | $25.00 | $0.002500 | $10.00 | $15.00 | 58.3% | Alerts coming soon |
GPT-4.1 | OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT-4.1 | Kimi K2 (Groq) | Cheaper |
|---|---|---|---|
| Input (standard) | $2.00/M | $1.00/M | Kimi K2 (Groq) |
| Output | $8.00/M | $3.00/M | Kimi K2 (Groq) |
| Cached input | $0.50/M | N/A | — |
| Batch input | $1.00/M | N/A | — |
| Batch output | $4.00/M | N/A | — |
Prices last verified: 2026-03-06 – 2026-03-08
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 | GPT-4.1Monthly | Kimi K2 (Groq)Monthly | GPT-4.1Per request | Kimi K2 (Groq)Per request |
|---|---|---|---|---|
| 1K requests/mo | $6.00 | $2.50 | $0.006000 | $0.002500 |
| 10K requests/mo | $60.00 | $25.00 | $0.006000 | $0.002500 |
| 100K requests/mo | $600.00 | $250.00 | $0.006000 | $0.002500 |
| 1M requests/mo | $6,000.00 | $2,500.00 | $0.006000 | $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 GPT-4.1
by OpenAI
- RAG / Semantic search
- Document summarization
- Code generation
Input / 1M tokens
$2.00/M
Output / 1M tokens
$8.00/M
Context window
1,047,576
Tier
premium
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 | GPT-4.1 | Kimi K2 (Groq) |
|---|---|---|
| Context window | 1,047,576 tokens | 256,000 tokens |
| Max output tokens | 32,768 tokens | 32,768 tokens |
| Performance tier | Premium | Premium |
| Vision / image input | Yes | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | 10,000 | 30 |
GPT-4.1 notes
1M token context window enables entire codebases in context.
Kimi K2 (Groq) notes
Moonshot AI's flagship model on Groq hardware.
Frequently Asked Questions
Is GPT-4.1 cheaper than Kimi K2 (Groq)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Kimi K2 (Groq) costs $250.00/month versus $600.00/month for GPT-4.1 — a 58% 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, GPT-4.1 or Kimi K2 (Groq)?
GPT-4.1 has a larger context window at 1,047,576 tokens, compared to 256,000 tokens for Kimi K2 (Groq). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do GPT-4.1 and Kimi K2 (Groq) support the Batch API?
GPT-4.1 supports the Batch API (50% discount for async processing), while Kimi K2 (Groq) does not. If your workload tolerates up to 24-hour latency, routing to GPT-4.1 with batch pricing could significantly cut costs versus Kimi K2 (Groq)'s standard rate.
Which model offers better prompt caching?
GPT-4.1 supports prompt caching at $0.50/M for cached input, while Kimi K2 (Groq) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-4.1's caching capability can substantially reduce effective costs.
What are the best use cases for GPT-4.1 vs Kimi K2 (Groq)?
Both models are well-suited for RAG / Semantic search, Code generation. GPT-4.1 is particularly strong for Document summarization. Kimi K2 (Groq) is favored for similar workflows. 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 GPT-4.1 vs Kimi K2 (Groq)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-4.1 costs $0.006000 per request and Kimi K2 (Groq) costs $0.002500 per request. At 100,000 requests/month, that translates to $600.00 and $250.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT-4.1 vs Kimi K2 (Groq): Summary
When comparing GPT-4.1 and Kimi K2 (Groq) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Kimi K2 (Groq) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $250.00/month, compared to $600.00/month for GPT-4.1.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-4.1 charges $2.00/M for input tokens and $8.00/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 GPT-4.1 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: GPT-4.1 supports up to 1,047,576 tokens in a single request, versus 256,000 tokens for Kimi K2 (Groq). 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
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