GLM 5 Turbo vs Mercury 2
GLM 5 Turbo leads Mercury 2 on the Artificial Analysis Intelligence Index, 26.6 to 10.8, and Mercury 2 costs 5.3x less per output token ($0.75 vs $4.00 per million). Updated October 22, 2026; 16 benchmarks have a result for both.
GLM 5 Turbo or Mercury 2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5 Turbo for a larger context window (203K against 128K tokens) and work measured by ALE-Bench, where it leads.
- Shared results
- 16
- GLM 5 Turbo only
- 0
- Mercury 2 only
- 26
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GLM 5 Turbo
GLM 5 Turbo leads, 26.6 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
GLM 5 Turbo
GLM 5 Turbo leads, 1262 against 1036.
Same board, both measured
Long documents
Listed context window
GLM 5 Turbo
GLM 5 Turbo takes 203K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
GLM 5 Turbo $0.0032, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, Mercury 2 not benchmarked.
- Widest category
- Web design, 29.6 points apart on average over 8 shared benchmarks.
- Widest single gap
- Design Arena: 3D: GLM 5 Turbo 1247 against Mercury 2 982, 33.1 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against Mercury 2 $0.75 per million output tokens, 5.3x apart.
- Context window
- GLM 5 Turbo takes 203K tokens, Mercury 2 128K.
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 5 Turbo | Bars | Mercury 2 | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Web design | 8 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1171 | Only Mercury 2 measured |
| AA Coding Index | Not measured | 31.1 | Only Mercury 2 measured |
| SciCode | Not measured | 37.7% | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 26.5% | GLM 5 Turbo |
| WeirdML | Not measured | 43.2% | Only Mercury 2 measured |
| ALE-Bench | 634.0 | 785.6 | Mercury 2 |
| LMArena Text: coding | Not measured | 1390 | Only Mercury 2 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mercury 2 measured |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | Not measured | 1199 | Only Mercury 2 measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | 10.8 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.6 | Only Mercury 2 measured |
| τ²-Bench Telecom | 98.5% | 70.8% | GLM 5 Turbo |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | 77.0% | GLM 5 Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | 17.1% | GLM 5 Turbo |
| LMArena Text: hard prompts | Not measured | 1362 | Only Mercury 2 measured |
| LMArena Text: expert | Not measured | 1358 | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | Not measured | 1374 | Only Mercury 2 measured |
| Neither model has a result on the other 17 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1343 | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1363 | Only Mercury 2 measured |
| LMArena Text: business and finance | Not measured | 1349 | Only Mercury 2 measured |
| Neither model has a result on the other 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | 1036 | GLM 5 Turbo |
| Design Arena: UI components | 1260 | 996 | GLM 5 Turbo |
| Design Arena: game dev | 1248 | 984 | GLM 5 Turbo |
| Design Arena: data viz | 1264 | 1009 | GLM 5 Turbo |
| Design Arena: 3D | 1247 | 982 | GLM 5 Turbo |
| Design Arena: all code categories | 1261 | 1021 | GLM 5 Turbo |
| Design Arena: SVG | 1205 | 998 | GLM 5 Turbo |
| Design Arena: ASCII art | 1160 | 988 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Mercury 2 | Leader |
|---|---|---|---|
| IFBench | 73.2% | 69.8% | GLM 5 Turbo |
| Long context reasoning (AA-LCR) | 71.7% | 43.7% | GLM 5 Turbo |
| LMArena Text | Not measured | 1354 | Only Mercury 2 measured |
| LMArena Text: instruction following | Not measured | 1328 | Only Mercury 2 measured |
| LMArena Text: creative writing | Not measured | 1286 | Only Mercury 2 measured |
| LMArena Text: English | Not measured | 1378 | Only Mercury 2 measured |
| LMArena Text: non-English | Not measured | 1330 | Only Mercury 2 measured |
| LMArena Text: Chinese | Not measured | 1414 | Only Mercury 2 measured |
| LMArena Text: Russian | Not measured | 1304 | Only Mercury 2 measured |
| LMArena Text: multi-turn | Not measured | 1357 | Only Mercury 2 measured |
| LMArena Text: longer queries | Not measured | 1329 | Only Mercury 2 measured |
| LMArena Text: writing and language | Not measured | 1300 | Only Mercury 2 measured |
| LMArena Text: entertainment and media | Not measured | 1314 | Only Mercury 2 measured |
| Neither model has a result on the other 33 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Mercury 2 | 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
Mercury 2 costs less
Repository review
50K input + 3K output tokens
Mercury 2 costs less
Agent loop
200K input + 10K output tokens
Mercury 2 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 5 Turbo | Inception Mercury 2 |
|---|---|---|
| Maker | Z.ai | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | March 15, 2026 | March 4, 2026 |
| Context window | 203K | 128K |
| Input $/Mtok | $1.20 | $0.25 |
| Output $/Mtok | $4.00 | $0.75 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 Turbo better than Mercury 2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5 Turbo for a larger context window (203K against 128K tokens) and work measured by ALE-Bench, where it leads.
Which is cheaper, GLM 5 Turbo or Mercury 2?
GLM 5 Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5 Turbo or Mercury 2?
GLM 5 Turbo, with 203K tokens against 128K.
How many benchmarks is the GLM 5 Turbo vs Mercury 2 comparison based on?
16 benchmarks have a result for both models as of October 22, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.