LLM Reference

DeepSeek R1 0528 vs Kimi K2.5

DeepSeek R1 0528 (2025) and Kimi K2.5 (2026) compare a standalone API model against a coding-specialized model. DeepSeek R1 0528 ships a 130k-token context window, while Kimi K2.5 ships a 256k-token context window. On MMLU PRO, Kimi K2.5 leads by 2.1 pts. On pricing, Kimi K2.5 costs $0.44/1M input tokens versus $0.50/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: DeepSeek R1 0528 is standalone API model, while Kimi K2.5 is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalDeepSeek R1 0528Kimi K2.5
Product typeStandalone API modelCoding-specialized model
Best forreasoning-heavy apps and provider-routed productioncustom coding agents, code generation, and tool loops
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window130k256k
Cheapest output$2.15/1M tokens$2/1M tokens
Provider routes7 tracked10 tracked
Shared benchmarks5 sharedMMLU PRO leader

Decision tradeoffs

Choose DeepSeek R1 0528 when...
  • DeepSeek R1 0528 uniquely exposes Reasoning and Code execution in local model data.
  • Local decision data tags DeepSeek R1 0528 for Coding, RAG, and Agents.
Choose Kimi K2.5 when...
  • Kimi K2.5 holds a shared-benchmark lead on MMLU PRO, ahead by 2.1 points.
  • Kimi K2.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Kimi K2.5 has the lower cheapest tracked output price at $2/1M tokens.
  • Kimi K2.5 has broader tracked provider coverage for fallback and route flexibility.
  • Kimi K2.5 uniquely exposes Vision, Multimodal, and JSON / Tool use in local model data.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Kimi K2.5

DeepSeek R1 0528

$938

Cheapest tracked route/tier: OpenRouter

Kimi K2.5

$852

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $85.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek R1 0528 -> Kimi K2.5
  • Provider overlap exists on Fireworks AI, OpenRouter, and Together AI; start route-level A/B tests there.
  • Kimi K2.5 is $0.15/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Reasoning and Code execution before moving production traffic.
  • Kimi K2.5 adds Vision, Multimodal, and JSON / Tool use in local capability data.
Kimi K2.5 -> DeepSeek R1 0528
  • Provider overlap exists on Together AI, Fireworks AI, and Novita AI; start route-level A/B tests there.
  • DeepSeek R1 0528 is $0.15/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Vision, Multimodal, and JSON / Tool use before moving production traffic.
  • DeepSeek R1 0528 adds Reasoning and Code execution in local capability data.

Specs

Specification
Released2025-05-282026-03-15
Context window130k256k
Parameters685B total, 37B active (MoE)1T (MoE, 384 experts)
ArchitectureDecoder OnlyMixture of Experts
LicenseMITOSI-approvedProprietary
OpennessOpen sourceProprietary
WeightsUnknownNot released
CodeUnknownUnknown
Commercial useCommercial use: permittedCommercial use: conditional
Knowledge cutoff--

Pricing and availability

Pricing attributeDeepSeek R1 0528Kimi K2.5
Input price$0.50/1M tokens$0.44/1M tokens
Output price$2.15/1M tokens$2/1M tokens
Providers

Capabilities

CapabilityDeepSeek R1 0528Kimi K2.5
VisionNoYes
MultimodalNoYes
ReasoningYesNo
JSON / Tool useNoYes
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkDeepSeek R1 0528Kimi K2.5
MMLU PRO85.087.1
SWE-bench Verified57.676.8
Google-Proof Q&A81.087.9
AIME 202587.596.1
LiveCodeBench73.385.0

Continue comparing

Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.