Model comparison
Gemini 3.6 Flash vs GLM 5.2
Google against Z.ai, compared on context, price, and verified benchmark results.
Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Gemini 3.6 Flash
Balanced
Z.ai
GLM 5.2
Balanced · Open weights
| Specification | Gemini 3.6 Flash | GLM 5.2 |
|---|---|---|
| Provider | Z.ai | |
| Tier | Balanced | Balanced |
| Context window | 1M | 1M |
| Max output | 64K | Winner: 128K |
| Input / 1M tokens | Winner: $0.75 | $1.40 |
| Output / 1M tokens | Winner: $3.75 | $4.40 |
| Weights | Closed | Open |
| Parameters | Not disclosedUnverified | open MoE |
| Reasoning levels | low, medium, high | low, high, max |
| Modalities | text, image, video, audio, pdf | text |
| API model id | gemini-3.6-flash | glm-5.2 |
| Released | July 21, 2026 | March 15, 2026 |
| Artificial Analysis Intelligence Index (2026-08-14) | Winner: 54 | 50 |
| Terminal-Bench 2.1 (2026-07) | 78 | Not verifiedUnverified |
| DeepSWE 1.1 (2026-07) | 48.6 | Not verifiedUnverified |
| Humanity's Last Exam (2026-08) | 51.2 | Not verifiedUnverified |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
- 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
- 2026-08: Google DeepMind model evaluation report (vendor, HLE-Verified full set)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
- 2026-07: Google DeepMind model evaluation report (vendor, quoting Datacurve leaderboard; 3.7 report shows 49 — rounding conflict preserved)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
Pricing tiers: Gemini 3.6 Flash: $0.75/$3.75 per MTok (intro through 2026-12-31, then $1.50/$7.50). Multimodal input. · GLM 5.2: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs.
Gemini 3.6 Flash
Gemini 3.6 Flash is Google's balanced multimodal Flash tier with a 1M-token context.
Best for
- Multimodal pipelines
- High-volume processing
- Video and audio input
Watch out
Superseded by 3.7 Flash on quality; still a solid mid-tier.
GLM 5.2
GLM 5.2 is Zhipu's previous-generation open-weight model with strong cost-performance.
Best for
- Open-weight deployments
- Reasoning
- Cost-sensitive work
Watch out
Superseded by GLM 5.3 (Coding Plan 5.2/5.1 requests route to 5.3). Parameter count: sources disagree.
When the cheaper one wins
Gemini 3.6 Flash is cheaper on output at $3.75 per million tokens against $4.40 for GLM 5.2 — about 1.2×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 4/5 core specs verified on both sides — Not published for at least one side: parameter count.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 6 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- Gemini 3.6 Flash: Google — Gemini 3.6 Flash (accessed 2026-08-29)
- Gemini 3.6 Flash: Google Cloud Gemini pricing (accessed 2026-08-29)
- GLM 5.2: HuggingFace — Z.ai (GLM) (accessed 2026-08-29)
- GLM 5.2: Z.ai (accessed 2026-08-29)
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- GLM 5.2 vs Grok 4.5
- Amazon Nova 2 Pro vs Gemini 3.6 Flash
- Amazon Nova 2 Pro vs GLM 5.2
Diving deeper on one model? Gemini 3.6 Flash · GLM 5.2
Common questions
Gemini 3.6 Flash vs GLM 5.2
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.6 Flash or GLM 5.2 cheaper for input?
Gemini 3.6 Flash is cheaper at $0.75 per million input tokens, against $1.40 for GLM 5.2 — roughly 1.9× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.6 Flash has tiered pricing: $0.75/$3.75 per MTok (intro through 2026-12-31, then $1.50/$7.50). Multimodal input. GLM 5.2 has tiered pricing: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs.
Is Gemini 3.6 Flash or GLM 5.2 cheaper for output?
Gemini 3.6 Flash is cheaper at $3.75 per million output tokens, against $4.40 for GLM 5.2 — roughly 1.2× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.6 Flash has tiered pricing: $0.75/$3.75 per MTok (intro through 2026-12-31, then $1.50/$7.50). Multimodal input. GLM 5.2 has tiered pricing: Z.ai's per-token table lists $1.40/$4.40 per MTok (same list as 5.3). Open-weight, text-only; 1M context, 128K max output per Z.ai docs.
Which has the larger context window, Gemini 3.6 Flash or GLM 5.2?
Both accept about 1M tokens of context, so document length will not decide between them.
Do Gemini 3.6 Flash and GLM 5.2 support the same reasoning levels?
Gemini 3.6 Flash exposes low, medium, high, while GLM 5.2 exposes low, high, max.
Should I use Gemini 3.6 Flash or GLM 5.2?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. Gemini 3.6 Flash suits multimodal pipelines; GLM 5.2 suits open-weight deployments.
Can I self-host Gemini 3.6 Flash or GLM 5.2?
GLM 5.2 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 3.6 Flash is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Gemini 3.6 Flash costs $0.75 per 1M tokens versus $1.40 for GLM 5.2 — a 1.9x difference at the headline tier.
- Measured capability: Gemini 3.6 Flash leads Artificial Analysis Intelligence Index 54 to 50 (measured 2026-08-14).
- Deployment: GLM 5.2 publishes weights you can self-host; the other is API-only.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.