Model comparison
DeepSeek-V3.1-Terminus vs Grok 4.5
Grok 4.5 is the stronger model overall, scoring 55.0 to 42.6 on the Noometry Index. DeepSeek-V3.1-Terminus costs 6.3× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
DeepSeekSummary
- They share 16 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and Grok 4.5 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.0 to 25.7.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 83.5% for Grok 4.5.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Grok 4.5 | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 42.6 | 55.0 |
| Released | 2025-09-22 | 2026-07-08 |
| Weights | Open | Proprietary |
| Context window | 164K | 500K |
| Max output | 66K | 500K |
| Input $ / M tokens | $0.30 | $2 |
| Output $ / M tokens | $1 | $6 |
| Results tracked | 16 | 52 |
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Category by category
Coding Grok 4.5 leads
DeepSeek-V3.1-Terminus: 41.5 (#114), Grok 4.5: 51.7 (#34)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| SciCode | 40.6% | 54.1% |
| LMArena Coding | 1426 | 1473 |
| ALE-Bench | 745.17 | 1,309 |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| LMArena WebDev | — | 1552 |
| WeirdML | — | 46.4% |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Grok 4.5: 44.4 (#15)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| APEX-Agents | — | 56.2% |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
| Vending-Bench 2 | — | 3,887 |
Reasoning Grok 4.5 leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Grok 4.5: 56.0 (#23)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 83.5% |
| CritPt | 1.7% | 15.4% |
| LMArena Hard Prompts | 1427 | 1462 |
| DTBench | 81.3% | 96.5% |
| LMCA | 28.6% | 45.2% |
| ARC-AGI-2 | — | 52.6% |
| SimpleBench | — | 70% |
| NYT Connections (extended) | — | 79.9% |
| ARC-AGI-1 | — | 87.2% |
| Chess Puzzles | — | 36% |
| Surface Evolver Bench | — | 74.4% |
| Epoch Capabilities Index | — | 154.02 |
Math Grok 4.5 leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Grok 4.5: 60.7 (#29)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Math | 1402 | 1457 |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| OTIS Mock AIME 2024-2025 | — | 97.8% |
| ProofBench | — | 31% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Grok 4.5: 62.3 (#21)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| GPQA Diamond | — | 93.4% |
| SimpleQA Verified | — | 48.3% |
| LMArena Expert | — | 1466 |
Multimodal Not comparable
DeepSeek-V3.1-Terminus: —, Grok 4.5: 37.8 (#63)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1287 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |
Multilingual Grok 4.5 leads
DeepSeek-V3.1-Terminus: 52.3 (#87), Grok 4.5: 54.5 (#43)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Non-English | 1407 | 1439 |
| LMArena Russian | 1434 | 1447 |
| LMArena Chinese | — | 1497 |
| LMArena French | — | 1458 |
| LMArena German | — | 1448 |
| LMArena Japanese | — | 1425 |
| LMArena Korean | — | 1402 |
| LMArena Spanish | — | 1452 |
Instruction Following Grok 4.5 leads
DeepSeek-V3.1-Terminus: 74.4 (#96), Grok 4.5: 76.3 (#45)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | 1406 | 1446 |
Long Context Grok 4.5 leads
DeepSeek-V3.1-Terminus: 43.5 (#88), Grok 4.5: 44.8 (#54)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | 1426 | 1463 |
Writing & Preference Grok 4.5 leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Grok 4.5: 65.9 (#40)
| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Text | 1420 | 1448 |
| LMArena Creative Writing | 1404 | 1442 |
| LMArena Multi-Turn | 1411 | 1457 |
| EQ-Bench Creative Writing | — | 1579 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Grok 4.5?
Grok 4.5 is the stronger model overall, scoring 55.0 to 42.6 on the Noometry Index. DeepSeek-V3.1-Terminus costs 6.3× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1-Terminus or Grok 4.5?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; Grok 4.5 lists at $2 and $6.
Is DeepSeek-V3.1-Terminus or Grok 4.5 better for coding?
Grok 4.5 scores higher on coding benchmarks: 51.7 versus 41.5 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Grok 4.5 share?
16 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Grok 4.5 has 52.