LLM Reference

DeepSeek V3 Base vs GLM-5V-Turbo

DeepSeek V3 Base (2024) and GLM-5V-Turbo (2026) are frontier reasoning models from DeepSeek and Zhipu AI. DeepSeek V3 Base ships a 128k-token context window, while GLM-5V-Turbo ships a 200k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

GLM-5V-Turbo is safer overall; choose DeepSeek V3 Base when provider fit matters.

Decision scorecard

Local evidence first
SignalDeepSeek V3 BaseGLM-5V-Turbo
Best forgeneral production evaluationreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitLong contextRAG, Agents, and Long context
Context window128k200k
Cheapest output-$4/1M tokens
Provider routes0 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose DeepSeek V3 Base when...
  • Local decision data tags DeepSeek V3 Base for Long context.
Choose GLM-5V-Turbo when...
  • GLM-5V-Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GLM-5V-Turbo has broader tracked provider coverage for fallback and procurement flexibility.
  • GLM-5V-Turbo uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags GLM-5V-Turbo for RAG, Agents, and Long context.

Monthly cost at traffic

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

DeepSeek V3 Base

Unavailable

No complete token price in local provider data

GLM-5V-Turbo

$1,960

Cheapest tracked route/tier: OpenRouter

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

DeepSeek V3 Base -> GLM-5V-Turbo
  • No overlapping tracked provider route is sourced for DeepSeek V3 Base and GLM-5V-Turbo; plan for SDK, billing, or endpoint changes.
  • GLM-5V-Turbo adds Vision, Multimodal, and Reasoning in local capability data.
GLM-5V-Turbo -> DeepSeek V3 Base
  • No overlapping tracked provider route is sourced for GLM-5V-Turbo and DeepSeek V3 Base; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.

Specs

Specification
Released2024-12-262026-04-01
Context window128k200k
Parameters671B total, 37B active (MoE)744B total, 40B active
Architecturemixture of expertsmixture of experts
LicenseMIT(OSI)MIT(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff2024-072025-11

Pricing and availability

Pricing attributeDeepSeek V3 BaseGLM-5V-Turbo
Input price-$1.20/1M tokens
Output price-$4/1M tokens
Providers-

Capabilities

CapabilityDeepSeek V3 BaseGLM-5V-Turbo
VisionNoYes
MultimodalNoYes
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: GLM-5V-Turbo, multimodal input: GLM-5V-Turbo, reasoning mode: GLM-5V-Turbo, function calling: GLM-5V-Turbo, tool use: GLM-5V-Turbo, and structured outputs: GLM-5V-Turbo. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: DeepSeek V3 Base has no token price sourced yet and GLM-5V-Turbo has $1.20/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose DeepSeek V3 Base when provider fit are central to the workload. Choose GLM-5V-Turbo when reasoning depth, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, DeepSeek V3 Base or GLM-5V-Turbo?

GLM-5V-Turbo supports 200k tokens, while DeepSeek V3 Base supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is DeepSeek V3 Base or GLM-5V-Turbo open source?

DeepSeek V3 Base is listed under MIT. GLM-5V-Turbo is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, DeepSeek V3 Base or GLM-5V-Turbo?

GLM-5V-Turbo has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, DeepSeek V3 Base or GLM-5V-Turbo?

GLM-5V-Turbo has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for reasoning mode, DeepSeek V3 Base or GLM-5V-Turbo?

GLM-5V-Turbo has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run DeepSeek V3 Base and GLM-5V-Turbo?

DeepSeek V3 Base is available on the tracked providers still being sourced. GLM-5V-Turbo is available on OpenRouter and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.