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GLM 4.6V vs Reka Edge

Reka Edge costs 9.0x less per output token than GLM 4.6V ($0.10 vs $0.90 per million). Updated October 22, 2026; no benchmark has tested both models yet.

GLM 4.6VZ.ai
Coding
No data
Overall
No data
Output $/M
$0.90
Reka EdgeReka
Coding
No data
Overall
No data
Output $/M
$0.10
vs $0.90 vs $0.10 per 1M output tokens. Reka Edge is 9.0x cheaper.

GLM 4.6V or Reka Edge: which to pick

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

Pick GLM 4.6V for a larger context window (131K against 16K tokens).

No benchmark has tested both yet. GLM 4.6V has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding; Reka Edge has none yet. 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 4.6V not benchmarked, Reka Edge 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 4.6V $0.90 against Reka Edge $0.10 per million output tokens, 9.0x apart.
Context window
GLM 4.6V takes 131K tokens, Reka Edge 16K.

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 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
LiveCodeBench (Artificial Analysis run)41.1%Not measuredOnly GLM 4.6V measured
Terminal-Bench Hard (Artificial Analysis run)14.4%Not measuredOnly GLM 4.6V measured
LMArena Text: coding1389Not measuredOnly GLM 4.6V measured
LMArena Text: software and IT1391Not measuredOnly GLM 4.6V 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 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
AA Intelligence Index11.2Not measuredOnly GLM 4.6V 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 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
τ²-Bench Telecom31.6%Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
Reasoning benchmarks for GLM 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
GPQA Diamond (Artificial Analysis run)71.9%Not measuredOnly GLM 4.6V measured
Humanity's Last Exam (Artificial Analysis run)9.6%Not measuredOnly GLM 4.6V measured
LMArena Text: hard prompts1367Not measuredOnly GLM 4.6V measured
LMArena Text: expert1371Not measuredOnly GLM 4.6V measured
LMArena Text: hard prompts in English1391Not measuredOnly GLM 4.6V measured
LMArena Vision: diagrams1182Not measuredOnly GLM 4.6V measured
LMArena Vision: homework1155Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Math benchmarks for GLM 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
AA Math Index85.3Not measuredOnly GLM 4.6V measured
AIME 2025 (Artificial Analysis run)85.3%Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 12 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Knowledge benchmarks for GLM 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
MMLU Pro (Artificial Analysis run)79.9%Not measuredOnly GLM 4.6V measured
LMArena Text: science1389Not measuredOnly GLM 4.6V measured
LMArena Text: medicine and healthcare1389Not measuredOnly GLM 4.6V measured
LMArena Text: legal and government1393Not measuredOnly GLM 4.6V measured
LMArena Text: business and finance1359Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 15 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards measured
General benchmarks for GLM 4.6V and Reka Edge
BenchmarkGLM 4.6VReka EdgeLeader
IFBench30.1%Not measuredOnly GLM 4.6V measured
Long context reasoning (AA-LCR)48.7%Not measuredOnly GLM 4.6V measured
LMArena Text1376Not measuredOnly GLM 4.6V measured
LMArena Text: instruction following1350Not measuredOnly GLM 4.6V measured
LMArena Text: creative writing1347Not measuredOnly GLM 4.6V measured
LMArena Vision1164Not measuredOnly GLM 4.6V measured
LMArena Text: English1395Not measuredOnly GLM 4.6V measured
LMArena Text: non-English1358Not measuredOnly GLM 4.6V measured
LMArena Text: Chinese1425Not measuredOnly GLM 4.6V measured
LMArena Text: Russian1339Not measuredOnly GLM 4.6V measured
LMArena Text: multi-turn1359Not measuredOnly GLM 4.6V measured
LMArena Text: longer queries1357Not measuredOnly GLM 4.6V measured
LMArena Text: writing and language1347Not measuredOnly GLM 4.6V measured
LMArena Text: entertainment and media1343Not measuredOnly GLM 4.6V measured
LMArena Vision: English1179Not measuredOnly GLM 4.6V measured
LMArena Vision: Chinese1217Not measuredOnly GLM 4.6V measured
LMArena Vision: reading text1171Not measuredOnly GLM 4.6V measured
LMArena Vision: creative writing1113Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 30 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 4.6V$0.0008Fits in one request
Reka Edge$0.0001Fits in one request

Reka Edge costs less

Repository review

50K input + 3K output tokens

GLM 4.6V$0.018Fits in one request
Reka Edge$0.0053Exceeds the context window

Reka Edge costs less

Agent loop

200K input + 10K output tokens

GLM 4.6V$0.069Exceeds the context window
Reka Edge$0.021Exceeds the context window

Reka Edge 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 4.6V and Reka Edge
SpecificationZ.ai GLM 4.6VReka Edge
MakerZ.aiReka
WeightsOpen weightsOpen weights
ReleasedDecember 8, 2025March 20, 2026
Context window131K16K
Input $/Mtok$0.30$0.10
Output $/Mtok$0.90$0.10
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6V better than Reka Edge for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.6V for a larger context window (131K against 16K tokens).

Which is cheaper, GLM 4.6V or Reka Edge?

GLM 4.6V costs $0.30 per million input tokens and $0.90 per million output tokens; Reka Edge costs $0.10 and $0.10. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.6V or Reka Edge?

GLM 4.6V, with 131K tokens against 16K.

Has any benchmark tested both GLM 4.6V and Reka Edge?

No benchmark has tested both yet. GLM 4.6V has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding; Reka Edge has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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