Gemini 2.5 Flash vs GLM 4.7 Flash
Updated October 21, 2026. 41 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Gemini 2.5 Flash has the edge where the context window is larger, 1.05M against 200K tokens, and where what matters is Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
- Shared results
- 41
- Gemini 2.5 Flash only
- 28
- GLM 4.7 Flash only
- 2
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Gemini 2.5 Flash
Gemini 2.5 Flash leads, 15.5 against 14.9.
Same board, both measured
Web design
Design Arena: websites
GLM 4.7 Flash
GLM 4.7 Flash leads, 1194 against 1074.
Same board, both measured
Long documents
Listed context window
Gemini 2.5 Flash
Gemini 2.5 Flash takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
Gemini 2.5 Flash $0.0015, GLM 4.7 Flash $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Flash has the number, $0.466.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash not benchmarked, GLM 4.7 Flash not benchmarked.
- Widest category
- Agentic work, 67.3 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Flash 31.6% against GLM 4.7 Flash 98.8%, 67.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against GLM 4.7 Flash $0.40 per million output tokens, 6.3x apart.
- Context window
- Gemini 2.5 Flash takes 1.05M tokens, GLM 4.7 Flash 200K.
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 | Gemini 2.5 Flash | Bars | GLM 4.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 0 | 7 | ||
| General | 17 | 1 | ||
| All shared boards | 31 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | Not measured | Only Gemini 2.5 Flash measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | Not measured | Only Gemini 2.5 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 22.0% | GLM 4.7 Flash |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: coding | 1423 | 1382 | Gemini 2.5 Flash |
| LMArena Text: software and IT | 1425 | 1389 | Gemini 2.5 Flash |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | 14.9 | Gemini 2.5 Flash |
| Epoch Capabilities Index | 142.9 | Not measured | Only Gemini 2.5 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 31.6% | 98.8% | GLM 4.7 Flash |
| BALROG | 33.5% | Not measured | Only Gemini 2.5 Flash measured |
| Vending-Bench 2 | $549 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.0% | 58.1% | Gemini 2.5 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 7.6% | Gemini 2.5 Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 60.5% | Only GLM 4.7 Flash measured |
| ARC-AGI | 33.3% | Not measured | Only Gemini 2.5 Flash measured |
| ARC-AGI-2 | 2.5% | Not measured | Only Gemini 2.5 Flash measured |
| SimpleBench | 41.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: hard prompts | 1422 | 1356 | Gemini 2.5 Flash |
| LMArena Text: expert | 1426 | 1357 | Gemini 2.5 Flash |
| LMArena Text: hard prompts in English | 1420 | 1369 | Gemini 2.5 Flash |
| LMArena Vision: diagrams | 1245 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: homework | 1244 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | Not measured | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | 73.3% | Not measured | Only Gemini 2.5 Flash measured |
| OTIS Mock AIME | Not measured | 58.3% | Only GLM 4.7 Flash measured |
| LMArena Text: math | 1411 | 1355 | Gemini 2.5 Flash |
| LMArena Text: mathematical work | 1422 | 1369 | Gemini 2.5 Flash |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.4% | Not measured | Only Gemini 2.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | 83.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: science | 1433 | 1358 | Gemini 2.5 Flash |
| LMArena Text: medicine and healthcare | 1428 | 1343 | Gemini 2.5 Flash |
| LMArena Text: legal and government | 1430 | 1357 | Gemini 2.5 Flash |
| LMArena Text: business and finance | 1404 | 1343 | Gemini 2.5 Flash |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | 1194 | GLM 4.7 Flash |
| Design Arena: UI components | 1005 | 1208 | GLM 4.7 Flash |
| Design Arena: game dev | 1005 | 1135 | GLM 4.7 Flash |
| Design Arena: data viz | 1060 | 1123 | GLM 4.7 Flash |
| Design Arena: 3D | 1021 | 1121 | GLM 4.7 Flash |
| Design Arena: all code categories | 1059 | 1178 | GLM 4.7 Flash |
| Design Arena: SVG | 1020 | 1038 | GLM 4.7 Flash |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 44.8% | Not measured | Only Gemini 2.5 Flash measured |
| MedScribe (Vals AI) | 83.0% | Not measured | Only Gemini 2.5 Flash measured |
| IFBench | 50.3% | 60.8% | GLM 4.7 Flash |
| Long context reasoning (AA-LCR) | 65.3% | 41.7% | Gemini 2.5 Flash |
| DTBench | 76.5% | Not measured | Only Gemini 2.5 Flash measured |
| LMCA | 27.5% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text | 1417 | 1351 | Gemini 2.5 Flash |
| LMArena Text: instruction following | 1405 | 1327 | Gemini 2.5 Flash |
| LMArena Text: creative writing | 1400 | 1296 | Gemini 2.5 Flash |
| LMArena Vision | 1235 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: English | 1418 | 1373 | Gemini 2.5 Flash |
| LMArena Text: non-English | 1409 | 1330 | Gemini 2.5 Flash |
| LMArena Text: Chinese | 1449 | 1403 | Gemini 2.5 Flash |
| LMArena Text: German | 1417 | 1336 | Gemini 2.5 Flash |
| LMArena Text: Japanese | 1396 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Korean | 1385 | 1283 | Gemini 2.5 Flash |
| LMArena Text: French | 1432 | 1332 | Gemini 2.5 Flash |
| LMArena Text: Spanish | 1422 | 1350 | Gemini 2.5 Flash |
| LMArena Text: Russian | 1415 | 1333 | Gemini 2.5 Flash |
| LMArena Text: Polish | 1413 | 1291 | Gemini 2.5 Flash |
| LMArena Text: multi-turn | 1408 | 1342 | Gemini 2.5 Flash |
| LMArena Text: longer queries | 1419 | 1345 | Gemini 2.5 Flash |
| LMArena Text: writing and language | 1405 | 1320 | Gemini 2.5 Flash |
| LMArena Text: entertainment and media | 1393 | 1304 | Gemini 2.5 Flash |
| LMArena Vision: English | 1239 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: Chinese | 1284 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: reading text | 1237 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: humor | 1225 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: captioning | 1277 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | 1252 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1241 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | GLM 4.7 Flash | 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 | Google Gemini 2.5 Flash | Z.ai GLM 4.7 Flash |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | January 19, 2026 |
| Context window | 1.05M | 200K |
| Input $/Mtok | $0.30 | $0.0653 |
| Output $/Mtok | $2.50 | $0.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $0.466 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than GLM 4.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Gemini 2.5 Flash has the edge where the context window is larger, 1.05M against 200K tokens, and where what matters is Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
Which is cheaper, Gemini 2.5 Flash or GLM 4.7 Flash?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for Gemini 2.5 Flash only.
Which has the bigger context window, Gemini 2.5 Flash or GLM 4.7 Flash?
Gemini 2.5 Flash, with 1.05M tokens against 200K.
How many benchmarks is the Gemini 2.5 Flash vs GLM 4.7 Flash comparison based on?
41 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 0 independent benchmarks and GLM 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.