GLM 5V Turbo vs Llama 3.3 70B Instruct
GLM 5V Turbo leads Llama 3.3 70B Instruct on the Artificial Analysis Intelligence Index, 23.5 to 7.7, and Llama 3.3 70B Instruct costs 5.6x less per output token ($0.72 vs $4.00 per million). Updated October 22, 2026; 34 benchmarks have a result for both.
GLM 5V Turbo or Llama 3.3 70B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for a larger context window (203K against 131K tokens).
- Shared results
- 34
- GLM 5V Turbo only
- 31
- Llama 3.3 70B Instruct only
- 18
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 7.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 5V Turbo has a Design Arena: websites result, 1230.
Directional only
Long documents
Listed context window
GLM 5V Turbo
GLM 5V Turbo takes 203K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.3 70B Instruct
GLM 5V Turbo $0.0032, Llama 3.3 70B Instruct $0.0008 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, Llama 3.3 70B Instruct not benchmarked.
- Widest category
- Agentic work, 71.9 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5V Turbo 98.5% against Llama 3.3 70B Instruct 26.6%, 71.9 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against Llama 3.3 70B Instruct $0.72 per million output tokens, 5.6x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, Llama 3.3 70B Instruct 131K.
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 5V Turbo | Bars | Llama 3.3 70B Instruct | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 34 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| AA Coding Index | Not measured | 11.9 | Only Llama 3.3 70B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 28.8% | Only Llama 3.3 70B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 3.0% | GLM 5V Turbo |
| WeirdML | Not measured | 14.4% | Only Llama 3.3 70B Instruct measured |
| LMArena Text: coding | 1466 | 1268 | GLM 5V Turbo |
| LMArena Text: software and IT | 1460 | 1273 | GLM 5V Turbo |
| LMArena WebDev: React | 1386 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | 1356 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo 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 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 7.7 | GLM 5V Turbo |
| Epoch Capabilities Index | Not measured | 127.3 | Only Llama 3.3 70B Instruct measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1124 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | 1149 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | 1134 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | 1267 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | 1070 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1127 | Not measured | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 98.5% | 26.6% | GLM 5V Turbo |
| BALROG | Not measured | 23.0% | Only Llama 3.3 70B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 31.9% | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.9% | 49.8% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 3.6% | GLM 5V Turbo |
| GPQA Diamond (Epoch AI run) | Not measured | 47.4% | Only Llama 3.3 70B Instruct measured |
| SimpleBench | Not measured | 19.9% | Only Llama 3.3 70B Instruct measured |
| LMArena Text: hard prompts | 1443 | 1257 | GLM 5V Turbo |
| LMArena Text: expert | 1453 | 1225 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1277 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: homework | 1273 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 7.7 | Only Llama 3.3 70B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 7.7% | Only Llama 3.3 70B Instruct measured |
| OTIS Mock AIME | Not measured | 5.1% | Only Llama 3.3 70B Instruct measured |
| MATH level 5 | Not measured | 41.6% | Only Llama 3.3 70B Instruct measured |
| LMArena Text: math | 1442 | 1267 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1267 | GLM 5V Turbo |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 71.3% | Only Llama 3.3 70B Instruct measured |
| MMLU | Not measured | 86.3% | Only Llama 3.3 70B Instruct measured |
| LMArena Text: science | 1448 | 1284 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1275 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1284 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1243 | GLM 5V Turbo |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: UI components | 1210 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: game dev | 1218 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: data viz | 1202 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: 3D | 1208 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: all code categories | 1228 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: SVG | 1151 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1117 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | GLM 5V Turbo | Llama 3.3 70B Instruct | Leader |
|---|---|---|---|
| IFBench | 61.1% | 47.1% | GLM 5V Turbo |
| Long context reasoning (AA-LCR) | 70.3% | 15.7% | GLM 5V Turbo |
| DTBench | Not measured | 59.5% | Only Llama 3.3 70B Instruct measured |
| LMCA | Not measured | 17.5% | Only Llama 3.3 70B Instruct measured |
| Fiction.LiveBench | Not measured | 33.3% | Only Llama 3.3 70B Instruct measured |
| LMArena Text | 1437 | 1274 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1242 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1250 | GLM 5V Turbo |
| LMArena Vision | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: English | 1454 | 1303 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1236 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1217 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1251 | GLM 5V Turbo |
| LMArena Text: Japanese | Not measured | 1150 | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Korean | 1397 | 1142 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1282 | GLM 5V Turbo |
| LMArena Text: Spanish | 1452 | 1269 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1252 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1259 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1280 | GLM 5V Turbo |
| LMArena Text: longer queries | 1438 | 1255 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1255 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1241 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: humor | 1268 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1252 | Not measured | Only GLM 5V Turbo measured |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo 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 | GLM 5V Turbo | Llama 3.3 70B Instruct | 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
Llama 3.3 70B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.3 70B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.3 70B Instruct 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 5V Turbo | Meta Llama 3.3 70B Instruct |
|---|---|---|
| Maker | Z.ai | Meta Llama |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | December 6, 2024 |
| Context window | 203K | 131K |
| Input $/Mtok | $1.20 | $0.45 |
| Output $/Mtok | $4.00 | $0.72 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than Llama 3.3 70B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5V Turbo for a larger context window (203K against 131K tokens).
Which is cheaper, GLM 5V Turbo or Llama 3.3 70B Instruct?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Llama 3.3 70B Instruct costs $0.45 and $0.72. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or Llama 3.3 70B Instruct?
GLM 5V Turbo, with 203K tokens against 131K.
How many benchmarks is the GLM 5V Turbo vs Llama 3.3 70B Instruct comparison based on?
34 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Llama 3.3 70B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.