Model comparison
DeepSeek-V3 vs Grok 4.20 Multi-Agent
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 39.5 on the Noometry Index. DeepSeek-V3 costs 3.9× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
DeepSeekSummary
- They share 17 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and Grok 4.20 Multi-Agent in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 20.5.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3 | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 39.5 | 46.2 |
| Released | 2024-12-26 | 2026-03-09 |
| Weights | Open | Proprietary |
| Context window | 164K | 1M |
| Max output | 164K | 30K |
| Input $ / M tokens | $0.24 | $1.25 |
| Output $ / M tokens | $0.90 | $2.50 |
| Results tracked | 60 | 20 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Too close to call
DeepSeek-V3: 42.3 (#106), Grok 4.20 Multi-Agent: 43.0 (#92)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1368 | 1457 |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |
Agentic & Tool Use Not comparable
DeepSeek-V3: —, Grok 4.20 Multi-Agent: —
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Search | — | 1204 |
| METR Time Horizons | 49.6% | — |
Reasoning Grok 4.20 Multi-Agent leads
DeepSeek-V3: 20.5 (#236), Grok 4.20 Multi-Agent: 43.9 (#48)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Hard Prompts | 1365 | 1448 |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 89.6% |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| Epoch Capabilities Index | 135.94 | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |
Math Grok 4.20 Multi-Agent leads
DeepSeek-V3: 32.1 (#219), Grok 4.20 Multi-Agent: 39.4 (#104)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1373 | 1442 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
Knowledge Grok 4.20 Multi-Agent leads
DeepSeek-V3: 37.5 (#155), Grok 4.20 Multi-Agent: 40.4 (#119)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1351 | 1445 |
| GPQA Diamond | 67.6% | — |
| MMLU-Pro | 72.3% | — |
| Confabulations | 26.1% | — |
| Vectara Hallucination Rate | 6.1% | — |
| GPQA (HELM) | 53.8% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |
Multimodal Not comparable
DeepSeek-V3: —, Grok 4.20 Multi-Agent: 40.5 (#48)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | — | 1259 |
Multilingual Grok 4.20 Multi-Agent leads
DeepSeek-V3: 48.5 (#143), Grok 4.20 Multi-Agent: 54.4 (#43)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1358 | 1440 |
| LMArena Chinese | 1391 | 1475 |
| LMArena French | 1385 | 1466 |
| LMArena German | 1374 | 1456 |
| LMArena Japanese | 1333 | 1405 |
| LMArena Korean | 1319 | 1416 |
| LMArena Russian | 1373 | 1457 |
| LMArena Spanish | 1358 | 1447 |
Instruction Following Grok 4.20 Multi-Agent leads
DeepSeek-V3: 72.8 (#130), Grok 4.20 Multi-Agent: 74.8 (#84)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1345 | 1420 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |
Long Context Grok 4.20 Multi-Agent leads
DeepSeek-V3: 34.0 (#253), Grok 4.20 Multi-Agent: 43.7 (#88)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1352 | 1431 |
| Fiction.LiveBench | 50% | — |
Writing & Preference Grok 4.20 Multi-Agent leads
DeepSeek-V3: 57.4 (#130), Grok 4.20 Multi-Agent: 64.0 (#59)
| Benchmark | DeepSeek-V3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1375 | 1450 |
| LMArena Creative Writing | 1364 | 1436 |
| LMArena Multi-Turn | 1389 | 1452 |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |
Frequently asked questions
Is DeepSeek-V3 better than Grok 4.20 Multi-Agent?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 39.5 on the Noometry Index. DeepSeek-V3 costs 3.9× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3 or Grok 4.20 Multi-Agent?
DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is DeepSeek-V3 or Grok 4.20 Multi-Agent better for coding?
They score almost the same on coding (42.3 vs 43.0); test both on your own repository before choosing.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 164K.
How many benchmarks do DeepSeek-V3 and Grok 4.20 Multi-Agent share?
17 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Grok 4.20 Multi-Agent has 20.