Model A

Google

60.5/100

Supported · Public rank #72

90% interval 49.0–72.0

Gemini 3.5 Flash-Lite vs GLM-5

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

GLM-5

Z.AI

62.16/100

Supported · Public rank #62

90% interval 51.5–72.8

Decision reading

GLM-5 has the higher public score estimate, 62.16 versus 60.5, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Coding work
Code generation, repair, and software-engineering tasks
GLM-5
GLM-5 leads on the public coding lane, 49.1 to 43.6, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3.5 Flash-Lite and GLM-5 are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

8 Gemini 3.5 Flash-Lite only

2 Shared

34 GLM-5 only

Shared results: 2
Gemini 3.5 Flash-Lite only: 8
GLM-5 only: 34
Like-for-like categories: 1 / 8

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Coding

Like-for-like

Gemini 3.5 Flash-Lite: 43.6; Supported · #121/183
GLM-5: 49.1; Supported · #80/183
Basis: BenchAlign lane · 4 vs 6 public rows
Reading: GLM-5 leads · intervals overlap

Agentic

Directional only

Gemini 3.5 Flash-Lite: 43.4; Estimated · #104/151
GLM-5: 50.0; Estimated · #65/151
Basis: BenchAlign lane · 3 vs 11 public rows
Reading: Directional only

Knowledge

Directional only

Gemini 3.5 Flash-Lite: 53.0; Supported · #71/181
GLM-5: 54.9; Estimated · #62/181
Basis: BenchAlign lane · 2 vs 6 public rows
Reading: Directional only

Reasoning

Not comparable

Gemini 3.5 Flash-Lite: 60.8; Unranked · 3 rankable rows
GLM-5: 51.6; Unranked · 4 rankable rows
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Gemini 3.5 Flash-Lite: Not ranked
GLM-5: 56.9; #7/7
Basis: Provisional lane · 0 vs 4 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Gemini 3.5 Flash-Lite: Not ranked
GLM-5: 48.7; #6/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Gemini 3.5 Flash-Lite: 76.1; #16/48
GLM-5: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Gemini 3.5 Flash-Lite: Not ranked
GLM-5: 88.3; #31/120
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemini 3.5 Flash-Lite and GLM-5
Category	Gemini 3.5 Flash-Lite	GLM-5	Basis	Reading
Coding	43.6Supported · #121/183	49.1Supported · #80/183	Like-for-likeBenchAlign lane · 4 vs 6 public rows	GLM-5 leads · intervals overlap
Agentic	43.4Estimated · #104/151	50.0Estimated · #65/151	Directional onlyBenchAlign lane · 3 vs 11 public rows	Directional only
Knowledge	53.0Supported · #71/181	54.9Estimated · #62/181	Directional onlyBenchAlign lane · 2 vs 6 public rows	Directional only
Reasoning	60.8Unranked · 3 rankable rows	51.6Unranked · 4 rankable rows	Not comparableProvisional lane · 1 vs 1 weighted rows	Not comparable
Math	Not ranked	56.9#7/7	Not comparableProvisional lane · 0 vs 4 weighted rows	Not comparable
Multilingual	Not ranked	48.7#6/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	76.1#16/48	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	88.3#31/120	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Terminal-Bench 2.0
Agentic
Gemini 3.5 Flash-Lite: 54%GLM-5: 56.2%Normalized gap 2.2Gemini 3.5 Flash-Lite source GLM-5 source
SWE-bench Pro
Coding
Gemini 3.5 Flash-Lite: 54.2%GLM-5: 55.1%Normalized gap 0.9Gemini 3.5 Flash-Lite source GLM-5 source

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Gemini 3.5 Flash-Lite: $0.00155; Fits in one request
GLM-5: $0.0026; Fits in one request

Gemini 3.5 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash-Lite: $0.0225; Fits in one request
GLM-5: $0.0596; Fits in one request

Gemini 3.5 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemini 3.5 Flash-Lite: $0.037; Fits in one request
GLM-5: $0.252; Does not fit in one request; Cached input priced at the published list-input rate

GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationGemini 3.5 Flash-LiteGLM-5

Context window

Maximum documented context; output-token limits may be lower.

Gemini 3.5 Flash-Lite

Google latest Gemini model guide

GLM-5

200K

API model ID

Gemini 3.5 Flash-Lite

gemini-3.5-flash-lite

Google Gemini 3.5 Flash-Lite model documentation

GLM-5

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemini 3.5 Flash-Lite

$0.03 per 1M cached input tokens

Google Gemini API pricing

GLM-5

Not published

Documented inputs

Gemini 3.5 Flash-Lite

text, image, video, audio, pdf

Google Gemini 3.5 Flash-Lite model documentation

GLM-5

Not sourced

Documented outputs

Gemini 3.5 Flash-Lite

text

Google Gemini 3.5 Flash-Lite model documentation

GLM-5

Not sourced

Provider availability

Gemini 3.5 Flash-Lite

Generally Available · Gemini API, Google AI Studio

Google latest Gemini model guide

GLM-5

Not sourced

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

GLM-5

Non-Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

GLM-5

Open Weight

License

Gemini 3.5 Flash-Lite

Proprietary

GLM-5

Open Weight

Release date

Gemini 3.5 Flash-Lite

2026-07-21

GLM-5

2026-03-01

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: GLM-5 has the higher public score estimate, 62.16 versus 60.5, but the 90% score intervals overlap.
Workload cost: Repository review: $0.0225 vs $0.0596. Cache-heavy agent loop: $0.037 vs $0.252.
Context tradeoff: Gemini 3.5 Flash-Lite has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence44 rows

Agentic

Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54%
Source
GLM-556.2%
Source
GLM-5 leads this result
OSWorld-Verified
Gemini 3.5 Flash-Lite74%
Source
GLM-5—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3.5 Flash-Lite50.2%
Source
GLM-5—
Not directly comparable
Claw-Eval
Gemini 3.5 Flash-Lite—
GLM-557.7%
Source
Not directly comparable
QwenClawBench
Gemini 3.5 Flash-Lite—
GLM-554.1%
Source
Not directly comparable
τ³-bench results
Gemini 3.5 Flash-Lite—
GLM-565.6%
Source
Not directly comparable
DeepPlanning
Gemini 3.5 Flash-Lite—
GLM-514.6%
Source
Not directly comparable
Toolathlon
Gemini 3.5 Flash-Lite—
GLM-538%
Source
Not directly comparable
MCP Atlas
Gemini 3.5 Flash-Lite—
GLM-531.1%
Source
Not directly comparable
MCP-Tasks
Gemini 3.5 Flash-Lite—
GLM-560.8%
Source
Not directly comparable
WideResearch
Gemini 3.5 Flash-Lite—
GLM-569.8%
Source
Not directly comparable
CyberGym
Gemini 3.5 Flash-Lite—
GLM-543.2%
Source
Not directly comparable
Gert Labs
Gemini 3.5 Flash-Lite—
GLM-550.99%
Source
Not directly comparable

Coding

Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54.0%
Source
GLM-5—
Not directly comparable
SWE-bench Pro
Gemini 3.5 Flash-Lite54.2%
Source
GLM-555.1%
Source
GLM-5 leads this result
LiveCodeBench (Vals)
Gemini 3.5 Flash-Lite79.0%
Source
GLM-5—
Not directly comparable
SWE-bench (Vals)
Gemini 3.5 Flash-Lite75.0%
Source
GLM-5—
Not directly comparable
SWE-bench Verified
Gemini 3.5 Flash-Lite—
GLM-577.8%
Source
Not directly comparable
SWE-bench Verified*
Gemini 3.5 Flash-Lite—
GLM-572.8%
Source
Not directly comparable
SWE Multilingual
Gemini 3.5 Flash-Lite—
GLM-573.3%
Source
Not directly comparable
SWE-Rebench
Gemini 3.5 Flash-Lite—
GLM-562.8%
Source
Not directly comparable
React Native Evals
Gemini 3.5 Flash-Lite—
GLM-574.8%
Source
Not directly comparable

Reasoning

MRCRv2
Gemini 3.5 Flash-Lite72.2%
Source
GLM-5—
Not directly comparable
LongBench v2
Gemini 3.5 Flash-Lite—
GLM-560.8%
Source
Not directly comparable
AI-Needle
Gemini 3.5 Flash-Lite—
GLM-563.3%
Source
Not directly comparable

Knowledge

GPQA Diamond (Vals)
Gemini 3.5 Flash-Lite83.8%
Source
GLM-5—
Not directly comparable
MMLU-Pro (Vals)
Gemini 3.5 Flash-Lite85.8%
Source
GLM-5—
Not directly comparable
GPQA
Gemini 3.5 Flash-Lite—
GLM-586%
Source
Not directly comparable
GPQA-D
Gemini 3.5 Flash-Lite—
GLM-586.0%
Source
Not directly comparable
SuperGPQA
Gemini 3.5 Flash-Lite—
GLM-566.8%
Source
Not directly comparable
MMLU-Pro
Gemini 3.5 Flash-Lite—
GLM-585.7%
Source
Not directly comparable
MMLU-Pro (Arcee)
Gemini 3.5 Flash-Lite—
GLM-585.8%
Source
Not directly comparable
HLE
Gemini 3.5 Flash-Lite—
GLM-550.4%
Source
Not directly comparable

Math

AIME26
Gemini 3.5 Flash-Lite—
GLM-595.8%
Source
Not directly comparable
AIME25 (Arcee)
Gemini 3.5 Flash-Lite—
GLM-593.3%
Source
Not directly comparable
HMMT Feb 2025
Gemini 3.5 Flash-Lite—
GLM-597.5%
Source
Not directly comparable
HMMT Nov 2025
Gemini 3.5 Flash-Lite—
GLM-596.9%
Source
Not directly comparable
HMMT Feb 2026
Gemini 3.5 Flash-Lite—
GLM-586.4%
Source
Not directly comparable
MMAnswerBench
Gemini 3.5 Flash-Lite—
GLM-582.5%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Gemini 3.5 Flash-Lite—
GLM-516.434%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Gemini 3.5 Flash-Lite—
GLM-52.100%
Source
Not directly comparable

Multilingual

MMLU-ProX
Gemini 3.5 Flash-Lite—
GLM-583.1%
Source
Not directly comparable
NOVA-63
Gemini 3.5 Flash-Lite—
GLM-555.1%
Source
Not directly comparable

Instruction following

IFEval
Gemini 3.5 Flash-Lite—
GLM-592.6%
Source
Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash-Lite or GLM-5?

GLM-5 has the higher public score estimate, 62.16 versus 60.5, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3.5 Flash-Lite or GLM-5?

GLM-5 leads the public coding lane, 49.1 to 43.6, with Supported evidence for both models, although the 90% intervals overlap.

Which is better for agentic tasks, Gemini 3.5 Flash-Lite or GLM-5?

GLM-5 scores higher for agentic tasks on the public lane, 50 to 43.4. Gemini 3.5 Flash-Lite and GLM-5 are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Gemini 3.5 Flash-Lite or GLM-5?

For the stated presets, chat costs $0.00155 on Gemini 3.5 Flash-Lite and $0.0026 on GLM-5; repository review costs $0.0225 and $0.0596; the cache-heavy agent loop costs $0.037 and $0.252. GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 3.5 Flash-Lite or GLM-5?

Gemini 3.5 Flash-Lite has the larger documented context window: 1M, compared with 200K.

Related comparisons

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Last updated September 4, 2026

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Gemini 3.5 Flash-Lite vs GLM-5

Which one for your work

Coding work

Long documents

Chat turn cost

Repository review cost

Agentic work

Cache-heavy agent loop cost

What is actually comparable

Category results, on a stated basis

Coding

Agentic

Knowledge

Reasoning

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Instruction following

Frequently asked questions

Which is better, Gemini 3.5 Flash-Lite or GLM-5?

Which is better for coding, Gemini 3.5 Flash-Lite or GLM-5?

Which is better for agentic tasks, Gemini 3.5 Flash-Lite or GLM-5?

Which costs less, Gemini 3.5 Flash-Lite or GLM-5?

Which has the larger context window, Gemini 3.5 Flash-Lite or GLM-5?

Related comparisons

Watch Gemini 3.5 Flash-Lite vs GLM-5