Model comparison
Seed 2.0 Pro vs Llama-3.3-70B-Instruct
Seed 2.0 Pro is the stronger model overall, scoring 43.2 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 7.3× less per token, which makes it the better buy when Seed 2.0 Pro's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
ByteDance Seed
MetaSummary
- They share 17 benchmarks with published results for both. Seed 2.0 Pro scores higher in 8 categories and Llama-3.3-70B-Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Seed 2.0 Pro leads 39.3 to 15.3.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.50 / $3 for Seed 2.0 Pro.
- Seed 2.0 Pro accepts more context: 256K tokens versus 128K.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.
Side by side
| Seed 2.0 Pro | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | ByteDance Seed | Meta |
| Noometry Index | 43.2 | 30.6 |
| Released | 2026-02-14 | 2024-12-06 |
| Weights | Proprietary | Open |
| Context window | 256K | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $0.50 | $0.10 |
| Output $ / M tokens | $3 | $0.32 |
| Results tracked | 20 | 43 |
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Category by category
Coding Seed 2.0 Pro leads
Seed 2.0 Pro: 43.5 (#86), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1472 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
Agentic & Tool Use Not comparable
Seed 2.0 Pro: —, Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
Reasoning Seed 2.0 Pro leads
Seed 2.0 Pro: 24.1 (#165), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 1453 | 1257 |
| SimpleBench | — | 19.9% |
| NYT Connections (extended) | 28.4% | — |
| CritPt | — | 0% |
| Thematic Generalization | 57.1% | — |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| Epoch Capabilities Index | — | 127.33 |
| ForecastBench | — | 58.6 |
| LiveBench | — | 50.2% |
Math Seed 2.0 Pro leads
Seed 2.0 Pro: 39.3 (#108), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1439 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
Knowledge Seed 2.0 Pro leads
Seed 2.0 Pro: 40.2 (#122), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1440 | 1225 |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| MMLU | — | 86.3% |
Multimodal Not comparable
Seed 2.0 Pro: 41.5 (#35), Llama-3.3-70B-Instruct: —
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1274 | — |
Multilingual Seed 2.0 Pro leads
Seed 2.0 Pro: 54.5 (#39), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1441 | 1236 |
| LMArena Chinese | 1489 | 1217 |
| LMArena French | 1471 | 1281 |
| LMArena German | 1442 | 1251 |
| LMArena Japanese | 1408 | 1150 |
| LMArena Korean | 1411 | 1143 |
| LMArena Russian | 1449 | 1252 |
| LMArena Spanish | 1460 | 1270 |
Instruction Following Seed 2.0 Pro leads
Seed 2.0 Pro: 74.5 (#91), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1414 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
Long Context Seed 2.0 Pro leads
Seed 2.0 Pro: 43.6 (#90), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1428 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Seed 2.0 Pro leads
Seed 2.0 Pro: 62.9 (#69), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Seed 2.0 Pro | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1448 | 1274 |
| LMArena Creative Writing | 1406 | 1250 |
| LMArena Multi-Turn | 1441 | 1280 |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Seed 2.0 Pro better than Llama-3.3-70B-Instruct?
Seed 2.0 Pro is the stronger model overall, scoring 43.2 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 7.3× less per token, which makes it the better buy when Seed 2.0 Pro's lead doesn't matter for your workload.
Which is cheaper, Seed 2.0 Pro or Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Seed 2.0 Pro lists at $0.50 and $3.
Is Seed 2.0 Pro or Llama-3.3-70B-Instruct better for coding?
Seed 2.0 Pro scores higher on coding benchmarks: 43.5 versus 31.0 in the Noometry coding category.
Which has the bigger context window?
Seed 2.0 Pro does, with 256K tokens against 128K.
How many benchmarks do Seed 2.0 Pro and Llama-3.3-70B-Instruct share?
17 benchmarks have published results for both models. Seed 2.0 Pro has 20 scored results on Noometry and Llama-3.3-70B-Instruct has 43.