GPT-3.5 Turbo (older v0613) vs Granite 4.2 8B
Granite 4.2 8B costs 10.0x less per output token than GPT-3.5 Turbo (older v0613) ($0.20 vs $2.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
GPT-3.5 Turbo (older v0613) or Granite 4.2 8B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-3.5 Turbo (older v0613) has results on GSM8K, MMLU and WinoGrande; Granite 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. Compare them on price and context instead.
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
No call
Only Granite 4.2 8B has a AA Intelligence Index result, 11.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Granite 4.2 8B has a AA Agentic Index result, 1.3.
Directional only
Long documents
Listed context window
Granite 4.2 8B
Granite 4.2 8B takes 131K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.2 8B
GPT-3.5 Turbo (older v0613) $0.0020, Granite 4.2 8B $0.0002 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo (older v0613) not benchmarked, Granite 4.2 8B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-3.5 Turbo (older v0613) $2.00 against Granite 4.2 8B $0.20 per million output tokens, 10.0x apart.
- Context window
- GPT-3.5 Turbo (older v0613) takes 4K tokens, Granite 4.2 8B 131K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 22.4 | Only Granite 4.2 8B measured |
| SciCode | Not measured | 31.5% | Only Granite 4.2 8B measured |
| LMArena Text: coding | Not measured | 1378 | Only Granite 4.2 8B measured |
| LMArena Text: software and IT | Not measured | 1366 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.1 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 63.1% | Only Granite 4.2 8B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.7% | Only Granite 4.2 8B 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 | 1344 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| GSM8K | 46.9% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| Neither model has a result on the other 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| MMLU | 68.9% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| LMArena Text: science | Not measured | 1335 | Only Granite 4.2 8B measured |
| LMArena Text: medicine and healthcare | Not measured | 1332 | 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 15 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Granite 4.2 8B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 45.0% | Only Granite 4.2 8B measured |
| WinoGrande | 81.6% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| LMArena Text | Not measured | 1319 | Only Granite 4.2 8B measured |
| LMArena Text: instruction following | Not measured | 1301 | Only Granite 4.2 8B measured |
| LMArena Text: creative writing | Not measured | 1235 | Only Granite 4.2 8B measured |
| LMArena Text: English | Not measured | 1337 | Only Granite 4.2 8B measured |
| LMArena Text: non-English | Not measured | 1300 | Only Granite 4.2 8B measured |
| LMArena Text: Chinese | Not measured | 1365 | Only Granite 4.2 8B measured |
| LMArena Text: Russian | Not measured | 1280 | Only Granite 4.2 8B measured |
| LMArena Text: multi-turn | Not measured | 1300 | Only Granite 4.2 8B measured |
| LMArena Text: longer queries | Not measured | 1324 | 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 35 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 | OpenAI GPT-3.5 Turbo (older v0613) | IBM Granite 4.2 8B |
|---|---|---|
| Maker | OpenAI | IBM Granite |
| Weights | No public weights listed | Open weights |
| Released | January 25, 2024 | August 31, 2026 |
| Context window | 4K | 131K |
| Input $/Mtok | $1.00 | $0.08 |
| Output $/Mtok | $2.00 | $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 GPT-3.5 Turbo (older v0613) better than Granite 4.2 8B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-3.5 Turbo (older v0613) or Granite 4.2 8B?
GPT-3.5 Turbo (older v0613) costs $1.00 per million input tokens and $2.00 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, GPT-3.5 Turbo (older v0613) or Granite 4.2 8B?
Granite 4.2 8B, with 131K tokens against 4K.
Has any benchmark tested both GPT-3.5 Turbo (older v0613) and Granite 4.2 8B?
No benchmark has tested both yet. GPT-3.5 Turbo (older v0613) has results on GSM8K, MMLU and WinoGrande; Granite 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. Compare them on price and context instead. Data as of October 23, 2026.