DeepSeek V3.2 vs GLM-5
DeepSeek V3.2 (2025) and GLM-5 (2026) are frontier reasoning models from DeepSeek and Zhipu AI. DeepSeek V3.2 ships a 160k-token context window, while GLM-5 ships a 200k-token context window. On SWE-bench Verified, GLM-5 leads by 7.8 pts. On pricing, DeepSeek V3.2 costs $0.25/1M input tokens versus $0.60/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V3.2 is ~138% cheaper at $0.25/1M; pay for GLM-5 only for reasoning depth.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.2 | GLM-5 |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 160k | 200k |
| Cheapest output | $0.38/1M tokens | $2.08/1M tokens |
| Provider routes | 7 tracked | 7 tracked |
| Shared benchmarks | 3 shared | SWE-bench Verified leader |
Decision tradeoffs
- DeepSeek V3.2 has the lower cheapest tracked output price at $0.38/1M tokens.
- DeepSeek V3.2 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.2 for Coding, RAG, and Agents.
- GLM-5 holds a shared-benchmark lead on SWE-bench Verified, ahead by 7.8 points.
- GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 uniquely exposes Reasoning and JSON / Tool use in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3.2
$296
Cheapest tracked route/tier: OpenRouter
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $704. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, OpenRouter, and NVIDIA NIM; start route-level A/B tests there.
- GLM-5 is $1.70/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- GLM-5 adds Reasoning and JSON / Tool use in local capability data.
- Provider overlap exists on Fireworks AI, NVIDIA NIM, and OpenRouter; start route-level A/B tests there.
- DeepSeek V3.2 is $1.70/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and JSON / Tool use before moving production traffic.
- DeepSeek V3.2 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-01 | 2026-02-11 |
| Context window | 160k | 200k |
| Parameters | 671B | 744B total, 40B active |
| Architecture | Decoder Only | Mixture of Experts |
| License | MITOSI-approved | MITOSI-approved |
| Openness | Open source | Open source |
| Weights | Unknown | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | - | 2025-11 |
Pricing and availability
| Pricing attribute | DeepSeek V3.2 | GLM-5 |
|---|---|---|
| Input price | $0.25/1M tokens | $0.60/1M tokens |
| Output price | $0.38/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.2 | GLM-5 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| JSON / Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3.2 | GLM-5 |
|---|---|---|
| SWE-bench Verified | 70.0 | 77.8 |
| Google-Proof Q&A | 84.0 | 86.0 |
| SWE-rebench | 60.9 | 62.8 |
Continue comparing
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Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.