R1 0528
by DeepSeekdeepseek/deepseek-r1-0528
LLMCompare cannot run R1 0528 yet.No route to this model is configured on this site yet. Its prices and parameters are listed below for reference.
See the models that can be run nowR1 0528 at a glance
- Context length
- 163,840 tokens
- Maximum output
- 32,768 tokens
- Accepts
- Text
- Returns
- Text
- Features
- JSON outputTool callingPrompt caching
- Reasoning effort levels
- Not supported
- Released
- 28 May 2025
- Knowledge cutoff
- 31 March 2025
Model facts synced from the OpenRouter model list on 21 Oct 2026.
R1 0528 pricing by route
A route is the service LLMCompare calls to reach the model. R1 0528 has 1 route. Prices are in US dollars.
| Route | On LLMCompare | Inputper 1M tokens | Outputper 1M tokens | Cache readper 1M tokens | Price verified on | Source |
|---|---|---|---|---|---|---|
| OpenRouterDefault | Not configured | $0.50 | $2.15 | $0.35 | openrouter.ai/deepseek/deepseek-r1-0528 |
The cost shown in an LLMCompare report is calculated from these prices as they were at the time of the run.
Cost calculator
Estimate what a batch of calls to R1 0528 costs. The starting numbers are examples. Change them to match your task.
Part of the input tokens above, billed at the cache read price.
- Cost per call
- $0.0016
- 2 credits
- Cost of 100 calls
- $0.1575
- 200 credits
Calculated from the OpenRouter prices verified on 21 Oct 2026. Credits are the cost plus a 20% service fee, at $0.001 per credit, rounded up for each call, with a minimum of 1 per call. A real run is charged for the usage the provider reports.
Parameters you can set
These are the parameters LLMCompare can set when it calls the model through OpenRouter.
| Parameter | Type | Range or options | Default |
|---|---|---|---|
temperature | Number | 0 to 2in steps of 0.1 | Provider default |
top_p | Number | 0 to 1in steps of 0.05 | Provider default |
max_tokens | Integer | 1 to 32,768 | Provider default |
seed | Integer | -2,147,483,648 to 4,294,967,295 | Provider default |
response_format | One of | textjson_object | Provider default |
About R1 0528
May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...
Description as published for this model. LLMCompare has not edited it.
Models to compare with R1 0528
Text models from the same provider and models at the nearest price. The order is not a ranking.
| Add to comparison | Model | Context | Max output | Input priceper 1M tokens | Output priceper 1M tokens | Features | Released | On LLMCompare |
|---|---|---|---|---|---|---|---|---|
DeepSeek V4 Pro 0813DeepSeekdeepseek/deepseek-v4-pro-0813 | 1.05M | 393k | $0.66 | $1.98 | ReasoningJSONToolsCache | No route yet | ||
DeepSeek V3 0324DeepSeekdeepseek/deepseek-chat-v3-0324 | 164k | 115k | $0.29 | $1.14 | JSONToolsCache | No route yet | ||
DeepSeek V3DeepSeekdeepseek/deepseek-chat | 164k | 16k | $0.2574 | $1.03 | JSONTools | No route yet | ||
Qwen3.5 397B A17BQwenqwen/qwen3.5-397b-a17b | 262k | 65.5k | $0.39 | $2.34 | JSONToolsVision | No route yet | ||
GLM 4.6Z.aiz-ai/glm-4.6 | 205k | 131k | $0.55 | $2.20 | JSONToolsCache | No route yet | ||
MiniMax M1MiniMaxminimax/minimax-m1 | 1M | 40k | $0.55 | $2.20 | Tools | No route yet |
Questions about R1 0528
- How much does R1 0528 cost?
- On the OpenRouter route, R1 0528 costs $0.50 per 1 million input tokens and $2.15 per 1 million output tokens, in US dollars. Input tokens that R1 0528 reads from the prompt cache cost $0.35 per 1 million tokens. LLMCompare verified this price on 21 Oct 2026.
- What is the context length of R1 0528?
- R1 0528 has a context length of 163,840 tokens and returns up to 32,768 output tokens in one call.
- What inputs does R1 0528 accept?
- R1 0528 accepts these inputs: Text. R1 0528 returns: Text.
- Can I test R1 0528 on my own data?
- Not yet. LLMCompare lists the prices and parameters of R1 0528, but no route to R1 0528 is configured on LLMCompare, so it cannot be selected for an evaluation.