Model comparison
Gemini 3.7 Flash vs GLM 5.3 Flash
Google against Z.ai, compared on context, price, and attributed benchmark results.
Recorded profile verification October 2, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below
Gemini 3.7 Flash
Budget
Z.ai
GLM 5.3 Flash
Balanced · Open weights
| Specification | Gemini 3.7 Flash | GLM 5.3 Flash |
|---|---|---|
| Provider | ||
| Provider | Z.ai | |
| Tier | ||
| Tier | Budget | Balanced |
| Context window | ||
| Context window | 1.05M | 1.05M |
| Max output | ||
| Max output | 66K | Not verifiedUnverified |
| Input / 1M tokens | ||
| Input / 1M tokens | $0.75 | Winner: $0.15 |
| Output / 1M tokens | ||
| Output / 1M tokens | $3.75 | Winner: $0.50 |
| Weights | ||
| Weights | Closed | Open |
| Parameters | ||
| Parameters | Not verifiedUnverified | 320B total / 18B active (MoE) |
| Reasoning levels | ||
| Reasoning levels | low, medium, high | low, high, max |
| Modalities | ||
| Modalities | text, image, video, audio, pdf | text, image, video, file |
| License | ||
| License | Not verifiedUnverified | MIT |
| API model id | ||
| API model id | gemini-3.7-flash | glm-5.3-flash |
| Released | ||
| Released | August 13, 2026 | August 26, 2026 |
| Terminal-Bench 2.1 · source date Gemini 3.7 Flash: 2026-08, GLM 5.3 Flash: 2026-08 (comparability not verified) | ||
| Terminal-Bench 2.1 · source date Gemini 3.7 Flash: 2026-08, GLM 5.3 Flash: 2026-08 (comparability not verified) | 85.8 | 84.3 |
| DeepSWE 1.1 · source date Gemini 3.7 Flash: 2026-08, GLM 5.3 Flash: 2026-08 (comparability not verified) | ||
| DeepSWE 1.1 · source date Gemini 3.7 Flash: 2026-08, GLM 5.3 Flash: 2026-08 (comparability not verified) | 65.3 | 63.4 |
| HLE-Verified · source date Gemini 3.7 Flash: 2026-08 | ||
| HLE-Verified · source date Gemini 3.7 Flash: 2026-08 | 53.6 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index · source date GLM 5.3 Flash: 2026-10-01 | ||
| Artificial Analysis Intelligence Index · source date GLM 5.3 Flash: 2026-10-01 | Not verifiedUnverified | 42 |
| Humanity's Last Exam · source date GLM 5.3 Flash: 2026-08 | ||
| Humanity's Last Exam · source date GLM 5.3 Flash: 2026-08 | Not verifiedUnverified | 55.3 |
Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
Where each score comes from, and how far it can be compared across models.
- Source date2026-10-01Artificial Analysis (GLM-5.3-Flash)
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check the cited source and its date.
- Source date2026-08GLM-5.3-Flash HF card (vendor, tools/full set; 300K context, 163,840 max generation, GPT-5.6-Luna medium judge)
Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise.
Comparable with caveatSubset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
- Source date2026-08Z.ai GLM-5.3-Flash blog (vendor, mini-swe-agent, 400K context)
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable
- Source date2026-08GLM-5.3-Flash HF card (vendor; Claude Code 2.1.207, 65,536 max generation, 6h timeout)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.
- Source date2026-08Google DeepMind model evaluation report (vendor; full 1,811-item HLE-Verified set) (Full 1,811-item verified/revised set; differs from original HLE and AA text-only HLE)
Expert reasoning on the verified and revised Humanity's Last Exam question set.
UnknownA distinct question set from original HLE and Artificial Analysis's text-only HLE. Shared dataset and publisher alone do not establish matching model effort, tools, filtering and run configuration; no quality winner is inferred without that evidence.
- Source date2026-08Google DeepMind model evaluation report (vendor, mini-swe-agent, high thinking)
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable
- Source date2026-08Google DeepMind model evaluation report (vendor, Terminus 2 harness)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.
Pricing tiers
Gemini 3.7 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid.
GLM 5.3 Flash: Z.ai API $0.15/$0.50 per MTok; cached input $0.03 and limited-time free cache storage. Hosted docs advertise 1M context and 128K output; the checkpoint config sets 1,048,576 context. An exact endpoint-specific numeric output ceiling is not separately verified. FlashX is a distinct $0.37/$1.25 endpoint; third-party prices require their own checks.
Gemini 3.7 Flash
Google describes Gemini 3.7 Flash as its efficient multimodal option for everyday coding and agentic tool use; the newer 3.8 is offered for more demanding workflows.
Best for
- High-volume multimodal
- Agent loops
- Cost-sensitive work
Watch out
Intro rates and cache storage double January 1, 2027. Minimal thinking errors; computer use is Preview. Measure accepted-task costs and token use before switching to the newer 3.8 rather than assuming uniform savings or quality.
GLM 5.3 Flash
Z.ai's multimodal MIT-licensed 320B/18B MoE checkpoint and hosted Flash endpoint, with always-enabled reasoning and publisher coding/agent evaluations.
Best for
- Cost-efficient long-context
- Multimodal input
- Coding agents
Watch out
The 320B weights require substantial hardware; memory depends on quantization, runtime and context. Effort low/high/max defaults to max. Flash is on Coding Plan with three times GLM-5.3 quota; FlashX is not on the plan. Half-point off-peak/weekend use applies to plan quota, not per-token API prices. Publisher evaluation generation budgets are not hosted API output caps.
When the cheaper one wins
GLM 5.3 Flash is cheaper on output at $0.50 per million tokens against $3.75 for Gemini 3.7 Flash — about 7.5×. 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. On DeepSWE 1.1, GLM 5.3 Flash is 63.4% Pass@1 at $0.48/task versus Gemini 3.7 Flash at 65.5% / $2.03/task. This compares standard short-context token rates, not total cost per accepted task. Include input, cache, context tiers, schedules, retries and review in your pilot.
Run the model pickerEvidence confidence: Medium
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.
- 3/5 core specs verified on both sides — Not published for at least one side: max output, parameter count.
- No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
- Verified within the last 90 days — Older of the two catalog checks was 25 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 3.7 Flash: Google primary profile — whole-record source check October 1 (accessed 2026-10-01)
- Gemini 3.7 Flash: Gemini current API pricing and cache-storage tiers (accessed 2026-10-01)
- Gemini 3.7 Flash: Google — Gemini 3.7 Flash (accessed 2026-08-29)
- Gemini 3.7 Flash: Google Cloud Gemini pricing (accessed 2026-08-29)
- GLM 5.3 Flash: GLM-5.3-Flash announcement (accessed 2026-10-01)
- GLM 5.3 Flash: Flash and FlashX hosted API scopes (accessed 2026-10-01)
- GLM 5.3 Flash: Z.ai first-party pricing (accessed 2026-10-01)
- GLM 5.3 Flash: Flash checkpoint settings and benchmark methods (accessed 2026-10-01)
- GLM 5.3 Flash: Flash exact MIT licence (accessed 2026-10-01)
- GLM 5.3 Flash: Flash checkpoint native context configuration (accessed 2026-10-01)
- GLM 5.3 Flash: Z.ai thinking controls and protocol mappings (accessed 2026-10-01)
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- Claude Haiku 4.5 vs Gemini 3.7 Flash
- Claude Opus 5 vs Gemini 3.7 Flash
- Claude Sonnet 5.5 vs GLM 5.3 Flash
Diving deeper on one model? Gemini 3.7 Flash · GLM 5.3 Flash
Common questions
Gemini 3.7 Flash vs GLM 5.3 Flash
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.7 Flash or GLM 5.3 Flash cheaper for input?
Is Gemini 3.7 Flash or GLM 5.3 Flash cheaper for output?
Which has the larger context window, Gemini 3.7 Flash or GLM 5.3 Flash?
Do Gemini 3.7 Flash and GLM 5.3 Flash support the same reasoning levels?
Should I use Gemini 3.7 Flash or GLM 5.3 Flash?
Can I self-host Gemini 3.7 Flash or GLM 5.3 Flash?
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: GLM 5.3 Flash costs $0.15 per 1M tokens versus $0.75 for Gemini 3.7 Flash — a 5x difference at the headline tier.
- Deployment: GLM 5.3 Flash publishes weights you can self-host; the other is API-only.
- Positioning: Gemini 3.7 Flash sits in the budget tier, GLM 5.3 Flash in the balanced tier. Compare accuracy, reliability, latency, and cost on representative tasks before choosing.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.