Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. On a tight budget at scale, DeepSeek V3.2 is the value pick.
DeepSeek V3.2 (DeepSeek) and GLM 5 (Z.ai) are two of the models people most often weigh against each other in 2026. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. They diverge most on price, context window and coding benchmarks — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V3.2 is about 3.6× cheaper on input ($0.28/$0.42 per 1M tokens vs $1/$3.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GLM 5 holds 1.5× more — 200K (~300 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Coding: GLM 5 leads SWE-Bench Verified by 4.7 points (73.1% vs 77.8%) — a real edge on hard, real-world software tasks.
Recency: GLM 5 is the newer model by about 2 months (released February 11, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V3.2
GLM 5
Provider
DeepSeek (China)
Z.ai (China)
Released
December 1, 2025
February 11, 2026
Context window
131K (~197 pages)
200K (~300 pages)
Price (in/out)
$0.28/$0.42 per 1M tokens
$1/$3.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
73.1%
77.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-context efficiency via DeepSeek Sparse Attention (DSA): DeepSeek V3.2 — A core design strength of DeepSeek V3.2.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes): DeepSeek V3.2 — A core design strength of DeepSeek V3.2.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386): DeepSeek V3.2 — A core design strength of DeepSeek V3.2.
Agentic planning and long-horizon coding workflows: GLM 5 — A core design strength of GLM 5.
Complex systems design and backend reasoning: GLM 5 — A core design strength of GLM 5.
Iterative self-correction on autonomous tasks: GLM 5 — A core design strength of GLM 5.
Lowest cost at scale: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GLM 5 — Its 200K window is about 1.5× larger, fitting roughly 300 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GLM 5 — Larger 200K window fits more in one prompt.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa): DeepSeek V3.2 — It is specifically built for that.
Anyone whose priority is agentic planning and long-horizon coding workflows: GLM 5 — That is its strongest area.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs are real: text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 out per million tokens, it sits in the budget price band.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V3.2 and GLM 5 overlap enough that the right pick depends on your specific job. DeepSeek V3.2 costs less per token; GLM 5 holds the larger context; and each leads in its own area — DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa), GLM 5 for agentic planning and long-horizon coding workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is DeepSeek V3.2 or GLM 5 better for coding?
On SWE-Bench Verified, DeepSeek V3.2 scores 73.1% and GLM 5 scores 77.8% — GLM 5 has the measurable edge.
Which is cheaper, DeepSeek V3.2 or GLM 5?
DeepSeek V3.2 is cheaper — $0.28/$0.42 per 1M tokens vs $1/$3.2 per 1M tokens, roughly 3.6× apart on input.
Which has the bigger context window?
GLM 5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek V3.2 and GLM 5 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V3.2, GLM 5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, DeepSeek V3.2 or GLM 5?
GLM 5 — released February 11, 2026, about 2 months after DeepSeek V3.2.
DeepSeek V3.2 vs GLM 5
DeepSeek · China | Z.ai · China · Updated June 2026
Quick verdict
Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. On a tight budget at scale, DeepSeek V3.2 is the value pick.
DeepSeek V3.2 (DeepSeek) and GLM 5 (Z.ai) are two of the models people most often weigh against each other in 2026. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. They diverge most on price, context window and coding benchmarks — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V3.2 is about 3.6× cheaper on input ($0.28/$0.42 per 1M tokens vs $1/$3.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GLM 5 holds 1.5× more — 200K (~300 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Coding: GLM 5 leads SWE-Bench Verified by 4.7 points (73.1% vs 77.8%) — a real edge on hard, real-world software tasks.
▸Recency: GLM 5 is the newer model by about 2 months (released February 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek V3.2
GLM 5
Provider
DeepSeek (China)
Z.ai (China)
Released
December 1, 2025
February 11, 2026
Context window
131K (~197 pages)
200K (~300 pages)
Price (in/out)
$0.28/$0.42 per 1M tokens
$1/$3.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
73.1%
77.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-context efficiency via DeepSeek Sparse Attention (DSA)
DeepSeek V3.2
A core design strength of DeepSeek V3.2.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes)
DeepSeek V3.2
A core design strength of DeepSeek V3.2.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386)
DeepSeek V3.2
A core design strength of DeepSeek V3.2.
Agentic planning and long-horizon coding workflows
GLM 5
A core design strength of GLM 5.
Complex systems design and backend reasoning
GLM 5
A core design strength of GLM 5.
Iterative self-correction on autonomous tasks
GLM 5
A core design strength of GLM 5.
Lowest cost at scale
DeepSeek V3.2
At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GLM 5
Its 200K window is about 1.5× larger, fitting roughly 300 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ DeepSeek V3.2
At $0.28/$0.42 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GLM 5
Larger 200K window fits more in one prompt.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa)
→ DeepSeek V3.2
It is specifically built for that.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
That is its strongest area.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs are real: text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 out per million tokens, it sits in the budget price band.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V3.2 and GLM 5 overlap enough that the right pick depends on your specific job. DeepSeek V3.2 costs less per token; GLM 5 holds the larger context; and each leads in its own area — DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa), GLM 5 for agentic planning and long-horizon coding workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V3.2 and GLM 5 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
On SWE-Bench Verified, DeepSeek V3.2 scores 73.1% and GLM 5 scores 77.8% — GLM 5 has the measurable edge.
Which is cheaper, DeepSeek V3.2 or GLM 5?
DeepSeek V3.2 is cheaper — $0.28/$0.42 per 1M tokens vs $1/$3.2 per 1M tokens, roughly 3.6× apart on input.
Which has the bigger context window?
GLM 5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek V3.2 and GLM 5 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V3.2, GLM 5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, DeepSeek V3.2 or GLM 5?
GLM 5 — released February 11, 2026, about 2 months after DeepSeek V3.2.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.