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GLM 5.3 Prime vs Granite 4.2 8B

Granite 4.2 8B costs 44.0x less per output token than GLM 5.3 Prime ($0.20 vs $8.80 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 Prime Replace Granite 4.2 8B
GLM 5.3 PrimeZ.ai
Coding
No data
Overall
No data
Output $/M
$8.80
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
vs $8.80 vs $0.20 per 1M output tokens. Granite 4.2 8B is 44.0x cheaper.

GLM 5.3 Prime or Granite 4.2 8B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 5.3 Prime for a larger context window (1M against 131K tokens).

Model AGLM 5.3 PrimeZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGranite 4.2 8BIBM GraniteNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. GLM 5.3 Prime has none yet; Granite 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GLM 5.3 Prime not benchmarked, Granite 4.2 8B not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GLM 5.3 Prime $8.80 against Granite 4.2 8B $0.20 per million output tokens, 44.0x apart.
Context window
GLM 5.3 Prime takes 1M tokens, Granite 4.2 8B 131K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
Coding benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
AA Coding IndexNot measured22.4Only Granite 4.2 8B measured
SciCodeNot measured31.5%Only Granite 4.2 8B measured
LMArena Text: codingNot measured1378Only Granite 4.2 8B measured
LMArena Text: software and ITNot measured1367Only Granite 4.2 8B measured
Neither model has a result on the other 39 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
AA Intelligence IndexNot measured11.1Only Granite 4.2 8B measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
AA Agentic IndexNot measured1.3Only Granite 4.2 8B measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Reasoning benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
GPQA Diamond (Artificial Analysis run)Not measured63.1%Only Granite 4.2 8B measured
Humanity's Last Exam (Artificial Analysis run)Not measured9.7%Only Granite 4.2 8B measured
LMArena Text: hard promptsNot measured1327Only Granite 4.2 8B measured
LMArena Text: expertNot measured1386Only Granite 4.2 8B measured
LMArena Text: hard prompts in EnglishNot measured1345Only Granite 4.2 8B measured
Neither model has a result on the other 18 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
Knowledge benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
LMArena Text: scienceNot measured1336Only Granite 4.2 8B measured
LMArena Text: medicine and healthcareNot measured1336Only Granite 4.2 8B measured
LMArena Text: legal and governmentNot measured1327Only Granite 4.2 8B measured
LMArena Text: business and financeNot measured1322Only Granite 4.2 8B measured
Neither model has a result on the other 16 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
General benchmarks for GLM 5.3 Prime and Granite 4.2 8B
BenchmarkGLM 5.3 PrimeGranite 4.2 8BLeader
Long context reasoning (AA-LCR)Not measured45.0%Only Granite 4.2 8B measured
LMArena TextNot measured1319Only Granite 4.2 8B measured
LMArena Text: instruction followingNot measured1300Only Granite 4.2 8B measured
LMArena Text: creative writingNot measured1236Only Granite 4.2 8B measured
LMArena Text: EnglishNot measured1337Only Granite 4.2 8B measured
LMArena Text: non-EnglishNot measured1301Only Granite 4.2 8B measured
LMArena Text: ChineseNot measured1367Only Granite 4.2 8B measured
LMArena Text: RussianNot measured1282Only Granite 4.2 8B measured
LMArena Text: multi-turnNot measured1301Only Granite 4.2 8B measured
LMArena Text: longer queriesNot measured1325Only Granite 4.2 8B measured
LMArena Text: writing and languageNot measured1269Only Granite 4.2 8B measured
LMArena Text: entertainment and mediaNot measured1271Only Granite 4.2 8B measured
Neither model has a result on the other 36 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GLM 5.3 Prime$0.0072Fits in one request
Granite 4.2 8B$0.0002Fits in one request

Granite 4.2 8B costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Prime$0.166Fits in one request
Granite 4.2 8B$0.0046Fits in one request

Granite 4.2 8B costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Prime$0.648Fits in one request
Granite 4.2 8B$0.018Exceeds the context window

Granite 4.2 8B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GLM 5.3 Prime and Granite 4.2 8B
SpecificationZ.ai GLM 5.3 PrimeIBM Granite 4.2 8B
MakerZ.aiIBM Granite
WeightsNo public weights listedOpen weights
ReleasedSeptember 23, 2026August 31, 2026
Context window1M131K
Input $/Mtok$2.80$0.08
Output $/Mtok$8.80$0.20
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Prime better than Granite 4.2 8B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5.3 Prime for a larger context window (1M against 131K tokens).

Which is cheaper, GLM 5.3 Prime or Granite 4.2 8B?

GLM 5.3 Prime costs $2.80 per million input tokens and $8.80 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 5.3 Prime or Granite 4.2 8B?

GLM 5.3 Prime, with 1M tokens against 131K.

Has any benchmark tested both GLM 5.3 Prime and Granite 4.2 8B?

No benchmark has tested both yet. GLM 5.3 Prime has none yet; Granite 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. Compare them on price and context instead. Data as of October 22, 2026.

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