DeepSeek V3 0324 vs Granite 4.2 8B
Granite 4.2 8B leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 11.1 to 9.7, and Granite 4.2 8B costs 5.3x less per output token ($0.20 vs $1.07 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
DeepSeek V3 0324 or Granite 4.2 8B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 7
- DeepSeek V3 0324 only
- 29
- Granite 4.2 8B only
- 20
- Like-for-like categories
- 5 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
Granite 4.2 8B
Granite 4.2 8B leads, 11.1 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
Granite 4.2 8B
Granite 4.2 8B leads, 1.3 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only DeepSeek V3 0324 has a GPQA Diamond result, 61.6%.
Directional only
Math
AIME
No call
Only DeepSeek V3 0324 has a AIME result, 52.2%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V3 0324 has a MMLU Pro result, 79.5%.
Directional only
Long documents
Listed context window
DeepSeek V3 0324
DeepSeek V3 0324 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.2 8B
DeepSeek V3 0324 $0.0008, Granite 4.2 8B $0.0002 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, Granite 4.2 8B not benchmarked.
- Widest category
- Coding, 4.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- SciCode: DeepSeek V3 0324 39.0% against Granite 4.2 8B 31.5%, 7.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Granite 4.2 8B $0.20 per million output tokens, 5.3x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, Granite 4.2 8B 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 | DeepSeek V3 0324 | Bars | Granite 4.2 8B | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 2 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | Not measured | Only DeepSeek V3 0324 measured |
| AA Coding Index | 21.2 | 22.4 | Granite 4.2 8B |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | 31.5% | DeepSeek V3 0324 |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | Not measured | Only DeepSeek V3 0324 measured |
| WeirdML | 36.1% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: coding | Not measured | 1378 | Only Granite 4.2 8B measured |
| LMArena Text: software and IT | Not measured | 1367 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 11.1 | Granite 4.2 8B |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 1.3 | Granite 4.2 8B |
| τ²-Bench Telecom | 47.1% | Not measured | Only DeepSeek V3 0324 measured |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | Not measured | Only DeepSeek V3 0324 measured |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 63.1% | DeepSeek V3 0324 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 9.7% | Granite 4.2 8B |
| GPQA Diamond (Epoch AI run) | 67.6% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: hard prompts | Not measured | 1327 | Only Granite 4.2 8B measured |
| LMArena Text: expert | Not measured | 1386 | Only Granite 4.2 8B measured |
| LMArena Text: hard prompts in English | Not measured | 1345 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| AIME | 52.2% | Not measured | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | Not measured | Only DeepSeek V3 0324 measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| MathArena | 7.1% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | Not measured | Only DeepSeek V3 0324 measured |
| LegalBench (Vals AI) | 77.7% | Not measured | Only DeepSeek V3 0324 measured |
| CorpFin (Vals AI) | 54.7% | Not measured | Only DeepSeek V3 0324 measured |
| TaxEval (Vals AI) | 71.1% | Not measured | Only DeepSeek V3 0324 measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: science | Not measured | 1336 | Only Granite 4.2 8B measured |
| LMArena Text: medicine and healthcare | Not measured | 1336 | Only Granite 4.2 8B measured |
| LMArena Text: legal and government | Not measured | 1327 | Only Granite 4.2 8B measured |
| LMArena Text: business and finance | Not measured | 1322 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 10 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | Leader |
|---|---|---|---|
| IFBench | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| Long context reasoning (AA-LCR) | 40.7% | 45.0% | Granite 4.2 8B |
| DTBench | 64.8% | Not measured | Only DeepSeek V3 0324 measured |
| LMCA | 15.5% | Not measured | Only DeepSeek V3 0324 measured |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text | Not measured | 1319 | Only Granite 4.2 8B measured |
| LMArena Text: instruction following | Not measured | 1300 | Only Granite 4.2 8B measured |
| LMArena Text: creative writing | Not measured | 1236 | Only Granite 4.2 8B measured |
| LMArena Text: English | Not measured | 1337 | Only Granite 4.2 8B measured |
| LMArena Text: non-English | Not measured | 1301 | Only Granite 4.2 8B measured |
| LMArena Text: Chinese | Not measured | 1367 | Only Granite 4.2 8B measured |
| LMArena Text: Russian | Not measured | 1282 | Only Granite 4.2 8B measured |
| LMArena Text: multi-turn | Not measured | 1301 | Only Granite 4.2 8B measured |
| LMArena Text: longer queries | Not measured | 1325 | Only Granite 4.2 8B measured |
| LMArena Text: writing and language | Not measured | 1269 | Only Granite 4.2 8B measured |
| LMArena Text: entertainment and media | Not measured | 1271 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 31 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Granite 4.2 8B | 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
Granite 4.2 8B costs less
Repository review
50K input + 3K output tokens
Granite 4.2 8B costs less
Agent loop
200K input + 10K output tokens
Granite 4.2 8B 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 | DeepSeek V3 0324 | IBM Granite 4.2 8B |
|---|---|---|
| Maker | DeepSeek | IBM Granite |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | August 31, 2026 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.27 | $0.08 |
| Output $/Mtok | $1.07 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Granite 4.2 8B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, DeepSeek V3 0324 or Granite 4.2 8B?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 0324 or Granite 4.2 8B?
DeepSeek V3 0324, with 164K tokens against 131K.
How many benchmarks is the DeepSeek V3 0324 vs Granite 4.2 8B comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and Granite 4.2 8B's on 0. Where only one model has a result, the page says so instead of naming a winner.