Head-to-head comparison

GPT-5.6 Luna vs. GLM-5.3-Flash

Compare published benchmark results from matching versions and cohorts, API pricing, and technical specifications. Any documented test setup differences remain visible.

shared result series: 24
distinct benchmarks: 24
latest retrieval: 2026-09-29

First modelSecond model

Specifications

General specifications

Release date, availability, context window, architecture, and published parameter counts at a glance. Undisclosed details remain marked as unavailable.

Specifications for GPT-5.6 Luna and GLM-5.3-Flash
Attribute	GPT-5.6 Luna	GLM-5.3-Flash
Provider	OpenAI	Z.ai
Released	Jul 9, 2026	Aug 26, 2026
Availability	Active	Open Source
Model type	Proprietary	Open Weights
Parameters	Not published	320B, 18B active
Architecture	Not published	Mixture of Experts
Context window	1,050,000 tokens	1,000,000 tokens
Knowledge cutoff	February 16, 2026	Not published
Technical sources	Model, Context, Knowledge cutoff	Model, Context

Pricing

API pricing compared

The table compares official standard API rates per 1M tokens, including published cache pricing. Batch, fast, priority, regional surcharges, tool calls, and cloud platform pricing are excluded.

API pricing for GPT-5.6 Luna and GLM-5.3-Flash
Price type	GPT-5.6 Luna	GLM-5.3-Flash
API input	$0.2 ≤272K / $0.4 >272K	$0.15
API output	$1.2 ≤272K / $1.8 >272K	$0.5
Cache read	$0.02 ≤272K / $0.04 >272K	$0.03
Cache write (5 min.)	$0.25 ≤272K / $0.5 >272K	Not listed
Cache write (1 hr.)	Not listed	Not listed
Price verified	09/22/2026 Source	09/22/2026 Source

GPT-5.6 LunaGLM-5.3-Flash

API inputUSD per 1M tokens, base tier

GPT-5.6 Luna$0.2

GLM-5.3-Flash$0.15

API outputUSD per 1M tokens, base tier

GPT-5.6 Luna$1.2

GLM-5.3-Flash$0.5

Cache readUSD per 1M tokens, base tier

GPT-5.6 Luna$0.02

GLM-5.3-Flash$0.03

Key to the marks:better valuebetter, but not conclusivetie

Pricing by provider

Direct developer pricing and provider endpoint tariffs routed through OpenRouter are listed separately. Prices are in USD per 1M tokens. Context-dependent direct tiers plus regional, Flex, Priority, and other OpenRouter tariffs remain individually identifiable.

Provider pricing for GPT-5.6 Luna and GLM-5.3-Flash
Model	Provider	Purchase route and tariff	Input per 1M tokens	Output per 1M tokens	Source
GPT-5.6 Luna	OpenAI	Direct from developerUp to 272,000 context tokens	$0.2	$1.2	Source09/22/2026
	OpenAI	Direct from developerAbove 272,000 context tokens	$0.4	$1.8	Source09/22/2026
	Amazon Bedrock	Via OpenRouteramazon-bedrock/us-east-1	$0.22	$1.32	Source10/15/2026
	Azure	Via OpenRouterazure	$0.2	$1.2	Source10/15/2026
	Azure	Via OpenRouterazure/eu	$0.22	$1.32	Source10/15/2026
	Azure	Via OpenRouterazure/us	$0.22	$1.32	Source10/15/2026
	OpenAI	Via OpenRouteropenai	$0.2	$1.2	Source10/15/2026
	OpenAI	Via OpenRouteropenai/fast	$0.4	$2.4	Source10/15/2026
	OpenAI	Via OpenRouteropenai/flex	Lowest listed price: $0.1	Lowest listed price: $0.6	Source10/15/2026
GLM-5.3-Flash	Z.ai	Direct from developerStandard API	$0.15	$0.5	Source09/22/2026
	AtlasCloud	Via OpenRouteratlas-cloud/fp8	$0.15	$0.5	Source10/15/2026
	CoreWeave	Via OpenRoutercoreweave/nvfp4	$0.15	$0.5	Source10/15/2026
	Crusoe	Via OpenRoutercrusoe/fp4	$0.15	$0.5	Source10/15/2026
	Decart	Via OpenRouterdecart/fp4	$0.093	$0.31	Source10/15/2026
	DeepInfra	Via OpenRouterdeepinfra/fp4	$0.075	$0.25	Source10/15/2026
	DigitalOcean	Via OpenRouterdigitalocean	$0.1312	$0.4375	Source10/15/2026
	Fireworks	Via OpenRouterfireworks	$0.15	$0.5	Source10/15/2026
	Fireworks	Via OpenRouterfireworks/us	$0.225	$0.75	Source10/15/2026
	Friendli	Via OpenRouterfriendli	$0.15	$0.5	Source10/15/2026
	Inceptron	Via OpenRouterinceptron/fp8	$0.108	$0.55	Source10/15/2026
	InferenceNet	Via OpenRouterinference-net/fp4	$0.083	$0.15	Source10/15/2026
	Makora	Via OpenRoutermakora	$0.14	$0.47	Source10/15/2026
	Modal	Via OpenRoutermodal/nvfp4	$0.15	$0.5	Source10/15/2026
	Morph	Via OpenRoutermorph/fp8	$0.074	$1	Source10/15/2026
	Near AI	Via OpenRouternear-ai/fp8	$0.08	$0.5	Source10/15/2026
	NextBit	Via OpenRouternextbit/fp4	$0.19	$0.6	Source10/15/2026
	Novita	Via OpenRouternovita/fp8	$0.084	$0.28	Source10/15/2026
	OpenInference	Via OpenRouteropen-inference/fp4	Lowest listed price: $0.036	$0.9	Source10/15/2026
	Parasail	Via OpenRouterparasail/fast	$0.1875	$0.625	Source10/15/2026
	Parasail	Via OpenRouterparasail/fp4	$0.15	$0.5	Source10/15/2026
	Reka	Via OpenRouterreka	$0.06	$1.6	Source10/15/2026
	Relace	Via OpenRouterrelace	$0.04	$0.5	Source10/15/2026
	Sail Research	Via OpenRoutersail-research/fp4	$0.045	$0.6	Source10/15/2026
	Sail Research	Via OpenRoutersail-research/us	$0.045	$0.6	Source10/15/2026
	SiliconFlow	Via OpenRoutersiliconflow/fp8	$0.15	$0.5	Source10/15/2026
	StreamLake	Via OpenRouterstreamlake/fp8	$0.0435	Lowest listed price: $0.145	Source10/15/2026
	Together	Via OpenRoutertogether	$0.15	$0.5	Source10/15/2026
	Wafer	Via OpenRouterwafer	$0.12	$0.5	Source10/15/2026
	Z.AI	Via OpenRouterz-ai/fp8	$0.15	$0.5	Source10/15/2026

Performance

Shared benchmarks

Only published results with the same benchmark version, task, metric, and comparison cohort are paired. Different reasoning levels, agents, harnesses, or output limits appear directly in the table.

Capability profile from matched benchmarks

Each axis averages directly matched benchmark families. A value of 100 means the stronger value within this pair, not a universal quality score.

GPT-5.6 Luna

GLM-5.3-Flash

Coding: 89 / 77.3 (7 benchmark families)

Reasoning: 100 / 94.2 (1 benchmark family)

Mathematics: 100 / 35 (1 benchmark family)

Knowledge: 100 / 100 (1 benchmark family)

Finance: 98.3 / 95.6 (4 benchmark families)

Legal: 66.5 / 100 (3 benchmark families)

Agentic tasks: 100 / 73 (2 benchmark families)

Multimodal: 98.9 / 100 (1 benchmark family)

24 matched rows from 23 benchmark families were considered. The radar shows 8 of 12 comparable categories.

GPT-5.6 LunaGLM-5.3-Flash

Code MigrationOverall. Higher is better. No documented setup difference

GPT-5.6 Luna44.55 %

GLM-5.3-Flash20.515 %

CyberBench v1.1Overall. Higher is better. No documented setup difference

GPT-5.6 Luna73.631 %

GLM-5.3-Flash67.857 %

EMBOverall. Higher is better. No documented setup difference

GPT-5.6 Luna67.116 %

GLM-5.3-Flash55.932 %

Finance Agent (v2)Overall. Higher is better. No documented setup difference

GPT-5.6 Luna55.044 %

GLM-5.3-Flash57.85 %

GPQA DiamondOverall. Higher is better. No documented setup difference

GPT-5.6 Luna91.666 %

GLM-5.3-Flash86.364 %

Harvey's Legal Agent BenchmarkOverall · Task fully resolved. Higher is better. No documented setup difference

GPT-5.6 Luna1.25 %

GLM-5.3-Flash6.667 %

IOIOverall. Higher is better. No documented setup difference

GPT-5.6 Luna61.778 %

GLM-5.3-Flash52.5 %

Legal Research BenchOverall · All-pass. Higher is better. No documented setup difference

GPT-5.6 Luna36.538 %

GLM-5.3-Flash45.192 %

LegalBenchOverall. Higher is better. No documented setup difference

GPT-5.6 Luna84.034 %

GLM-5.3-Flash83.928 %

MedScribeOverall. Higher is better. No documented setup difference

GPT-5.6 Luna84.391 %

GLM-5.3-Flash88.936 %

MMLU-ProOverall. Higher is better. No documented setup difference

GPT-5.6 Luna86.036 %

GLM-5.3-Flash86.059 %

MMMU-ProOverall. Higher is better. No documented setup difference

GPT-5.6 Luna85.029 %

GLM-5.3-Flash86.012 %

Key to the marks:better valuebetter, but not conclusivetie

Benchmark scores for GPT-5.6 Luna and GLM-5.3-Flash
Benchmark and task	GPT-5.6 Luna	GLM-5.3-Flash	Source
Code MigrationOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner44.55 %	20.515 %	Vals AI Source details Data as of: 09/27/2026
CyberBench v1.1Overall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better	Winner73.631 %	67.857 %	Vals AI Source details Data as of: 09/27/2026
EMBOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner67.116 %	55.932 %	Vals AI Source details Data as of: 09/27/2026
Finance Agent (v2)Overall Test details No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better	55.044 %	Winner57.85 %	Vals AI Source details Data as of: 09/27/2026
GPQA DiamondOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner91.666 %	86.364 %	Vals AI Source details Data as of: 09/01/2026
Harvey's Legal Agent BenchmarkOverall · Task fully resolved Test details No documented difference in the test setupVersion: 1Metric: task resolution rateScoring: Higher is better	1.25 %	Winner6.667 %	Vals AI Source details Data as of: 09/27/2026
IOIOverall Test details No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better	Winner61.778 %	52.5 %	Vals AI Source details Data as of: 09/27/2026
Legal Research BenchOverall · All-pass Test details No documented difference in the test setupVersion: 1Metric: all-pass rateScoring: Higher is better	36.538 %	Winner45.192 %	Vals AI Source details Data as of: 09/27/2026
LegalBenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner84.034 %	83.928 %	Vals AI Source details Data as of: 09/27/2026
MedScribeOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	84.391 %	Winner88.936 %	Vals AI Source details Data as of: 09/26/2026
MMLU-ProOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	86.036 %	Winner86.059 %	Vals AI Source details Data as of: 09/01/2026
MMMU-ProOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	85.029 %	Winner86.012 %	Vals AI Source details Data as of: 09/01/2026
ProgramBenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Tie0 %	Tie0 %	Vals AI Source details Data as of: 09/27/2026
ProofBenchOverall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better	Winner60 %	21 %	Vals AI Source details Data as of: 09/28/2026
SkillsBenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands	Winner60.447 %	40.159 %	Vals AI Source details Data as of: 09/27/2026
SWE-bench VerifiedOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner93 %	92 %	Vals AI Source details Data as of: 09/01/2026
Tax Agent BenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	60.815 %	Winner61.956 %	Vals AI Source details Data as of: 09/27/2026
TaxEval v2Overall Test details No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better	Winner76.166 %	75.593 %	Vals AI Source details Data as of: 09/01/2026
Terminal-Bench 2.1Overall Test details No documented difference in the test setupVersion: 2.1Metric: accuracyScoring: Higher is better	Winner79.026 %	62.921 %	Vals AI Source details Data as of: 09/27/2026
Terminal-Bench 4.0Overall Test details No documented difference in the test setupVersion: 4.0Metric: accuracyScoring: Higher is better	4.545 %	Winner19.697 %	Vals AI Source details Data as of: 09/27/2026
Terminal-Bench ScienceOverall Test details No documented difference in the test setupVersion: 0.1Metric: accuracyScoring: Higher is better	Winner5.714 %	0 %	Vals AI Source details Data as of: 09/27/2026
Vals IndexOverall Test details No documented difference in the test setupVersion: 2Metric: weighted index scoreScoring: Higher is better	Winner59.881 %	47.216 %	Vals AI Source details Data as of: 09/27/2026
Vibe Code Bench 1-100Overall Test details No documented difference in the test setupVersion: 1.0Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands	Winner22.594 %	16.033 %	Vals AI Source details Data as of: 09/22/2026
Vibe Code Bench v1.1Overall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands	Winner77.055 %	30.759 %	Vals AI Source details Data as of: 09/27/2026
Key to the marks:better valuebetter, but not conclusivetie

Our model tests

Our tests

SVG short test

One SVG prompt and fixed output settings. Captures are shown only with 0 reported reasoning tokens or documented lack of reasoning controls. Identical test conditions do not make the models' internal compute identical.

Shared test round: 4ae5d8eeb9a9

GPT-5.6 Luna

Unavailable in this round

GLM-5.3-Flash

Unavailable in this round

Earlier tests

Pelican on a bicycle

A community classic for free-form SVG drawing.

GPT-5.6 Luna

Reasoning (requested): high

Current attempt

Run date: Sep 7, 2026
API provider: openrouter
Requested API model: openai/gpt-5.6-luna
API model reported in response: openai/gpt-5.6-luna
Reasoning setting: high
Pinned endpoint: OpenAI | openai/gpt-5.6-luna-20260709
Temperature: Provider default
Token limit including reasoning: 8,192 tokens
Test protocol: community-visual-tests-v1
Technical checks: Passed, not a quality rating
Response time: 49.9 s

Visually reviewed. This individual test does not establish overall model quality.

GLM-5.3-Flash

Reasoning (requested): high

Current attempt

Run date: Oct 1, 2026
API provider: openrouter
Requested API model: z-ai/glm-5.3-flash
API model reported in response: z-ai/glm-5.3-flash
Reasoning setting: high
Pinned endpoint: Z.AI | z-ai/glm-5.3-flash-20260826
Temperature: Provider default
Token limit including reasoning: 8,192 tokens
Test protocol: community-visual-tests-v1
Technical checks: Passed, not a quality rating
Response time: 49.7 s

Visually reviewed. This individual test does not establish overall model quality.

Earlier attempts (1)

Sep 7, 2026API request failedReasoning setting: high

Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

How to read this comparison

Winning one benchmark is not an overall verdict

Your workload, budget, and required context length matter most. A coding benchmark says little about visual understanding or agent performance.

The standard price table uses direct developer rates. The provider comparison labels OpenRouter endpoints, regions, and special tariffs separately.

Every result links to its measurement source and retrieval date. Labels distinguish vendor reports, official benchmark leaderboards, and independent evaluations. Disputed or archived results are excluded.

More matchups

Compare GPT-5.6 Luna and GLM-5.3-Flash with other leading models using the same data and benchmark logic.

View the complete LLM comparison

GPT-5.6 Luna vs. GLM-5.3-Flash

Change model selection

General specifications

API pricing compared

Shared benchmarks

Capability profile from matched benchmarks

Our tests

SVG short test

GPT-5.6 Luna

GLM-5.3-Flash

Pelican on a bicycle

Winning one benchmark is not an overall verdict

Related LLM comparisons