GLM 4.7 Flash vs Grok 4.20
Grok 4.20 leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 25.7 to 14.9, and GLM 4.7 Flash costs 6.3x less per output token ($0.40 vs $2.50 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
GLM 4.7 Flash or Grok 4.20: which to pick
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for output tokens 6.3x cheaper ($0.40 vs $2.50 per million) and work measured by τ²-Bench Telecom or Design Arena: UI components, where it leads.
- Shared results
- 14
- GLM 4.7 Flash only
- 29
- Grok 4.20 only
- 41
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Grok 4.20 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.20
Grok 4.20 leads, 25.7 against 14.9.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Grok 4.20 has a GPQA Diamond result, 88.6%.
Directional only
Math
AIME
No call
Only Grok 4.20 has a AIME result, 96.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Grok 4.20 has a MMLU Pro result, 86.3%.
Directional only
Web design
Design Arena: websites
Grok 4.20
Grok 4.20 leads, 1229 against 1194.
Same board, both measured
Long documents
Listed context window
Grok 4.20
Grok 4.20 takes 2M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
GLM 4.7 Flash $0.0003, Grok 4.20 $0.0025 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Grok 4.20 has the number, $0.72.
Directional only
At a glance
- Coding index
- GLM 4.7 Flash not benchmarked, Grok 4.20 33.3 from 2 benchmarks.
- Widest category
- Reasoning, 30.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GLM 4.7 Flash 58.1% against Grok 4.20 91.1%, 33.0 points apart on a 0 to 100 scale.
- Output price
- GLM 4.7 Flash $0.40 against Grok 4.20 $2.50 per million output tokens, 6.3x apart.
- Context window
- GLM 4.7 Flash takes 200K tokens, Grok 4.20 2M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GLM 4.7 Flash | Bars | Grok 4.20 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 2 | ||
| Web design | 1 | 6 | ||
| General | 0 | 2 | ||
| All shared boards | 2 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | Not measured | 84.3% | Only Grok 4.20 measured |
| SWE-bench Verified (Vals AI) | Not measured | 72.2% | Only Grok 4.20 measured |
| Vibe Code Bench (Vals AI) | Not measured | 4.1% | Only Grok 4.20 measured |
| Code migration (Vals AI) | Not measured | 0.3% | Only Grok 4.20 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 44.2% | Only Grok 4.20 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.0% | 37.9% | Grok 4.20 |
| Terminal-Bench | Not measured | 57.3% | Only Grok 4.20 measured |
| WeirdML | Not measured | 52.3% | Only Grok 4.20 measured |
| LMArena Text: coding | 1382 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: software and IT | 1389 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.9 | 25.7 | Grok 4.20 |
| Epoch Capabilities Index | Not measured | 152.1 | Only Grok 4.20 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1144 | Only Grok 4.20 measured |
| Design Arena: agents building full-stack apps | Not measured | 1054 | Only Grok 4.20 measured |
| Design Arena: agents building mobile apps | Not measured | 1090 | Only Grok 4.20 measured |
| Design Arena: agents building Android apps | Not measured | 1052 | Only Grok 4.20 measured |
| Design Arena: agents building Godot games | Not measured | 1089 | Only Grok 4.20 measured |
| Design Arena: HTML slides | Not measured | 1180 | Only Grok 4.20 measured |
| Finance Agent (Vals AI) | Not measured | 28.5% | Only Grok 4.20 measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.0% | Only Grok 4.20 measured |
| Legal Research Bench (Vals AI) | Not measured | 13.9% | Only Grok 4.20 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 11.7% | Only Grok 4.20 measured |
| τ²-Bench Telecom | 98.8% | 93.0% | GLM 4.7 Flash |
| Vending-Bench 2 | Not measured | $4,663 | Only Grok 4.20 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 88.6% | Only Grok 4.20 measured |
| MMMU Pro (Vals AI) | Not measured | 83.5% | Only Grok 4.20 measured |
| GPQA Diamond (Artificial Analysis run) | 58.1% | 91.1% | Grok 4.20 |
| Humanity's Last Exam (Artificial Analysis run) | 7.6% | 34.5% | Grok 4.20 |
| GPQA Diamond (Epoch AI run) | 60.5% | Not measured | Only GLM 4.7 Flash measured |
| ARC-AGI | Not measured | 89.5% | Only Grok 4.20 measured |
| ARC-AGI-2 | Not measured | 65.1% | Only Grok 4.20 measured |
| LMArena Text: hard prompts | 1356 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: expert | 1357 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts in English | 1369 | Not measured | Only GLM 4.7 Flash measured |
| Kagi LLM Benchmark | Not measured | 75.0% | Only Grok 4.20 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| AIME | Not measured | 96.5% | Only Grok 4.20 measured |
| OTIS Mock AIME | 58.3% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: math | 1355 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: mathematical work | 1369 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.3% | Only Grok 4.20 measured |
| LegalBench (Vals AI) | Not measured | 77.7% | Only Grok 4.20 measured |
| CaseLaw (Vals AI) | Not measured | 54.4% | Only Grok 4.20 measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Grok 4.20 measured |
| TaxEval (Vals AI) | Not measured | 74.1% | Only Grok 4.20 measured |
| MortgageTax (Vals AI) | Not measured | 45.4% | Only Grok 4.20 measured |
| MedQA (Vals AI) | Not measured | 94.5% | Only Grok 4.20 measured |
| MedCode (Vals AI) | Not measured | 32.2% | Only Grok 4.20 measured |
| LMArena Text: science | 1358 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: medicine and healthcare | 1343 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: legal and government | 1357 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: business and finance | 1343 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| Design Arena: websites | 1194 | 1229 | Grok 4.20 |
| Design Arena: UI components | 1208 | 1199 | GLM 4.7 Flash |
| Design Arena: game dev | 1135 | 1192 | Grok 4.20 |
| Design Arena: data viz | 1123 | 1217 | Grok 4.20 |
| Design Arena: 3D | 1121 | 1193 | Grok 4.20 |
| Design Arena: all code categories | 1178 | 1221 | Grok 4.20 |
| Design Arena: SVG | 1038 | 1164 | Grok 4.20 |
| Design Arena: ASCII art | Not measured | 1174 | Only Grok 4.20 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 38.2% | Only Grok 4.20 measured |
| MedScribe (Vals AI) | Not measured | 63.4% | Only Grok 4.20 measured |
| Vals Multimodal Index | Not measured | 39.1% | Only Grok 4.20 measured |
| IFBench | 60.8% | 81.2% | Grok 4.20 |
| Long context reasoning (AA-LCR) | 41.7% | 69.0% | Grok 4.20 |
| DTBench | Not measured | 90.1% | Only Grok 4.20 measured |
| LMCA | Not measured | 38.7% | Only Grok 4.20 measured |
| CL-bench | Not measured | 22.2% | Only Grok 4.20 measured |
| CL-bench Life | Not measured | 11.9% | Only Grok 4.20 measured |
| LMArena Text | 1351 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: instruction following | 1327 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: creative writing | 1296 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: English | 1373 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: non-English | 1330 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Chinese | 1403 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: German | 1336 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Korean | 1283 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: French | 1332 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Spanish | 1350 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Russian | 1333 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Polish | 1291 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: multi-turn | 1342 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: longer queries | 1345 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: writing and language | 1320 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: entertainment and media | 1304 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.7 Flash | Grok 4.20 | Leader |
|---|---|---|---|
| Neither model has a result on 5 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 4.7 Flash costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 Flash 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.
| Specification | Z.ai GLM 4.7 Flash | SpaceXAI Grok 4.20 |
|---|---|---|
| Maker | Z.ai | xAI |
| Weights | Open weights | No public weights listed |
| Released | January 19, 2026 | March 31, 2026 |
| Context window | 200K | 2M |
| Input $/Mtok | $0.0653 | $1.25 |
| Output $/Mtok | $0.40 | $2.50 |
| Coding index | Not benchmarked | 33.3 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.72 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.7 Flash better than Grok 4.20 for coding?
Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 6.3x cheaper ($0.40 vs $2.50 per million) and work measured by τ²-Bench Telecom or Design Arena: UI components, where it leads.
Which is cheaper, GLM 4.7 Flash or Grok 4.20?
GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; Grok 4.20 costs $1.25 and $2.50. Cost per solved task is known for Grok 4.20 only.
Which has the bigger context window, GLM 4.7 Flash or Grok 4.20?
Grok 4.20, with 2M tokens against 200K.
How many benchmarks is the GLM 4.7 Flash vs Grok 4.20 comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and Grok 4.20's on 2. Where only one model has a result, the page says so instead of naming a winner.