Gemini 2.5 Flash Lite vs GLM 4.7
GLM 4.7 leads Gemini 2.5 Flash Lite on the Artificial Analysis Intelligence Index, 22.2 to 10.4, and Gemini 2.5 Flash Lite costs 5.5x less per output token ($0.40 vs $2.20 per million). Updated October 21, 2026; 23 benchmarks have a result for both.
Gemini 2.5 Flash Lite or GLM 4.7: which to pick
Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash Lite for output tokens 5.5x cheaper ($0.40 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).
- Shared results
- 23
- Gemini 2.5 Flash Lite only
- 7
- GLM 4.7 only
- 58
- Like-for-like categories
- 7 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 GLM 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 4.7
GLM 4.7 leads, 22.2 against 10.4.
Same board, both measured
Reasoning
GPQA Diamond
GLM 4.7
GLM 4.7 leads, 80.0% against 70.2%.
Same board, both measured
Math
AIME
GLM 4.7
GLM 4.7 leads, 93.3% against 42.1%.
Same board, both measured
Knowledge
MMLU Pro
GLM 4.7
GLM 4.7 leads, 82.7% against 79.1%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 4.7 has a Design Arena: websites result, 1226.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite $0.0003, GLM 4.7 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 4.7 has the number, $0.29.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, GLM 4.7 55.1 from 2 benchmarks.
- Widest category
- Agentic work, 76.9 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Flash Lite 19.0% against GLM 4.7 95.9%, 76.9 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against GLM 4.7 $2.20 per million output tokens, 5.5x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, GLM 4.7 205K.
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 Lite | Bars | GLM 4.7 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 1 | 3 | ||
| Knowledge | 2 | 5 | ||
| General | 1 | 2 | ||
| All shared boards | 4 | 19 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1435 | Only GLM 4.7 measured |
| AA Coding Index | Not measured | 45.3 | Only GLM 4.7 measured |
| LiveCodeBench (Vals AI) | 71.4% | 82.2% | GLM 4.7 |
| SWE-bench Verified (Vals AI) | Not measured | 69.4% | Only GLM 4.7 measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 89.4% | GLM 4.7 |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 31.8% | GLM 4.7 |
| Terminal-Bench | Not measured | 33.4% | Only GLM 4.7 measured |
| ALE-Bench | Not measured | 399.5 | Only GLM 4.7 measured |
| LMArena Text: coding | Not measured | 1454 | Only GLM 4.7 measured |
| LMArena Text: software and IT | Not measured | 1453 | Only GLM 4.7 measured |
| LMArena WebDev: React | Not measured | 1420 | Only GLM 4.7 measured |
| LMArena WebDev: HTML | Not measured | 1447 | Only GLM 4.7 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 22.2 | GLM 4.7 |
| Epoch Capabilities Index | 133.8 | 143.6 | GLM 4.7 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| Design Arena: agents building full-stack apps | Not measured | 1050 | Only GLM 4.7 measured |
| Design Arena: agents building mobile apps | Not measured | 1105 | Only GLM 4.7 measured |
| Design Arena: agents building Android apps | Not measured | 1112 | Only GLM 4.7 measured |
| Design Arena: agents building Godot games | Not measured | 1058 | Only GLM 4.7 measured |
| τ²-Bench Telecom | 19.0% | 95.9% | GLM 4.7 |
| Vending-Bench 2 | Not measured | $2,377 | Only GLM 4.7 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| BrowseComp-Plus | Not measured | 64.7% | Only GLM 4.7 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | 80.0% | GLM 4.7 |
| MMMU Pro (Vals AI) | 75.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 62.5% | 85.9% | GLM 4.7 |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 27.4% | GLM 4.7 |
| GPQA Diamond (Epoch AI run) | Not measured | 83.3% | Only GLM 4.7 measured |
| SimpleBench | Not measured | 47.7% | Only GLM 4.7 measured |
| Chess puzzles | Not measured | 21.0% | Only GLM 4.7 measured |
| LMArena Text: hard prompts | Not measured | 1443 | Only GLM 4.7 measured |
| LMArena Text: expert | Not measured | 1424 | Only GLM 4.7 measured |
| LMArena Text: hard prompts in English | Not measured | 1452 | Only GLM 4.7 measured |
| Kagi LLM Benchmark | 40.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| AIME | 42.1% | 93.3% | GLM 4.7 |
| MGSM (Vals AI) | 89.5% | 88.2% | Gemini 2.5 Flash Lite |
| AA Math Index | 53.3 | 95.0 | GLM 4.7 |
| AIME 2025 (Artificial Analysis run) | 53.3% | 95.0% | GLM 4.7 |
| OTIS Mock AIME | Not measured | 83.3% | Only GLM 4.7 measured |
| ProofBench | Not measured | 6.0% | Only GLM 4.7 measured |
| LMArena Text: math | Not measured | 1424 | Only GLM 4.7 measured |
| LMArena Text: mathematical work | Not measured | 1411 | Only GLM 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | 82.7% | GLM 4.7 |
| LegalBench (Vals AI) | 82.0% | 83.4% | GLM 4.7 |
| CaseLaw (Vals AI) | Not measured | 54.9% | Only GLM 4.7 measured |
| CorpFin (Vals AI) | 57.6% | 46.4% | Gemini 2.5 Flash Lite |
| TaxEval (Vals AI) | 66.2% | 68.8% | GLM 4.7 |
| MortgageTax (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | 88.9% | 93.7% | GLM 4.7 |
| MedCode (Vals AI) | 34.2% | 32.8% | Gemini 2.5 Flash Lite |
| MMLU Pro (Artificial Analysis run) | 75.9% | 85.6% | GLM 4.7 |
| SimpleQA Verified | Not measured | 32.2% | Only GLM 4.7 measured |
| LMArena Text: science | Not measured | 1457 | Only GLM 4.7 measured |
| LMArena Text: medicine and healthcare | Not measured | 1469 | Only GLM 4.7 measured |
| LMArena Text: legal and government | Not measured | 1444 | Only GLM 4.7 measured |
| LMArena Text: business and finance | Not measured | 1429 | Only GLM 4.7 measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1226 | Only GLM 4.7 measured |
| Design Arena: UI components | Not measured | 1199 | Only GLM 4.7 measured |
| Design Arena: game dev | Not measured | 1189 | Only GLM 4.7 measured |
| Design Arena: data viz | Not measured | 1195 | Only GLM 4.7 measured |
| Design Arena: 3D | Not measured | 1191 | Only GLM 4.7 measured |
| Design Arena: all code categories | Not measured | 1217 | Only GLM 4.7 measured |
| Design Arena: SVG | Not measured | 1143 | Only GLM 4.7 measured |
| Design Arena: ASCII art | Not measured | 1165 | Only GLM 4.7 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Gemini 2.5 Flash Lite | GLM 4.7 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 30.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedScribe (Vals AI) | 75.8% | 68.6% | Gemini 2.5 Flash Lite |
| IFBench | 49.9% | 67.9% | GLM 4.7 |
| Long context reasoning (AA-LCR) | 55.7% | 71.0% | GLM 4.7 |
| DTBench | 62.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LMCA | 18.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| CL-bench | Not measured | 15.9% | Only GLM 4.7 measured |
| CL-bench Life | Not measured | 10.9% | Only GLM 4.7 measured |
| LMArena Text | Not measured | 1435 | Only GLM 4.7 measured |
| LMArena Text: instruction following | Not measured | 1412 | Only GLM 4.7 measured |
| LMArena Text: creative writing | Not measured | 1401 | Only GLM 4.7 measured |
| LMArena Text: English | Not measured | 1453 | Only GLM 4.7 measured |
| LMArena Text: non-English | Not measured | 1417 | Only GLM 4.7 measured |
| LMArena Text: Chinese | Not measured | 1495 | Only GLM 4.7 measured |
| LMArena Text: German | Not measured | 1426 | Only GLM 4.7 measured |
| LMArena Text: Japanese | Not measured | 1439 | Only GLM 4.7 measured |
| LMArena Text: Korean | Not measured | 1399 | Only GLM 4.7 measured |
| LMArena Text: French | Not measured | 1432 | Only GLM 4.7 measured |
| LMArena Text: Spanish | Not measured | 1434 | Only GLM 4.7 measured |
| LMArena Text: Russian | Not measured | 1423 | Only GLM 4.7 measured |
| LMArena Text: Polish | Not measured | 1435 | Only GLM 4.7 measured |
| LMArena Text: multi-turn | Not measured | 1446 | Only GLM 4.7 measured |
| LMArena Text: longer queries | Not measured | 1432 | Only GLM 4.7 measured |
| LMArena Text: writing and language | Not measured | 1411 | Only GLM 4.7 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only GLM 4.7 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 | Gemini 2.5 Flash Lite | GLM 4.7 | 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
Gemini 2.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash Lite 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 Lite | Z.ai GLM 4.7 |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | Open weights |
| Released | July 22, 2025 | December 22, 2025 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $0.10 | $0.60 |
| Output $/Mtok | $0.40 | $2.20 |
| Coding index | Not benchmarked | 55.1 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.29 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash Lite better than GLM 4.7 for coding?
Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for output tokens 5.5x cheaper ($0.40 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).
Which is cheaper, Gemini 2.5 Flash Lite or GLM 4.7?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GLM 4.7 costs $0.60 and $2.20. Cost per solved task is known for GLM 4.7 only.
Which has the bigger context window, Gemini 2.5 Flash Lite or GLM 4.7?
Gemini 2.5 Flash Lite, with 1.05M tokens against 205K.
How many benchmarks is the Gemini 2.5 Flash Lite vs GLM 4.7 comparison based on?
23 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash Lite's coding index rests on 0 independent benchmarks and GLM 4.7's on 2. Where only one model has a result, the page says so instead of naming a winner.