GPT-3.5 Turbo (older v0613) vs Mercury 2
Mercury 2 costs 2.7x less per output token than GPT-3.5 Turbo (older v0613) ($0.75 vs $2.00 per million). Updated October 22, 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
- $0.75
GPT-3.5 Turbo (older v0613) or Mercury 2: 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; Mercury 2 on LMArena WebDev, AA Coding Index and SciCode. 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 Mercury 2 has a AA Intelligence Index result, 10.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
No call
Only Mercury 2 has a Design Arena: websites result, 1035.
Directional only
Long documents
Listed context window
Mercury 2
Mercury 2 takes 128K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
GPT-3.5 Turbo (older v0613) $0.0020, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo (older v0613) not benchmarked, Mercury 2 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 Mercury 2 $0.75 per million output tokens, 2.7x apart.
- Context window
- GPT-3.5 Turbo (older v0613) takes 4K tokens, Mercury 2 128K.
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 Index10 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1171 | Only Mercury 2 measured |
| AA Coding Index | Not measured | 31.1 | Only Mercury 2 measured |
| SciCode | Not measured | 37.7% | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 26.5% | Only Mercury 2 measured |
| WeirdML | Not measured | 43.2% | Only Mercury 2 measured |
| ALE-Bench | Not measured | 785.6 | Only Mercury 2 measured |
| LMArena Text: coding | Not measured | 1390 | Only Mercury 2 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mercury 2 measured |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | Not measured | 1199 | Only Mercury 2 measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 10.8 | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.6 | Only Mercury 2 measured |
| τ²-Bench Telecom | Not measured | 70.8% | Only Mercury 2 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.0% | Only Mercury 2 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 17.1% | Only Mercury 2 measured |
| LMArena Text: hard prompts | Not measured | 1362 | Only Mercury 2 measured |
| LMArena Text: expert | Not measured | 1358 | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | Not measured | 1374 | Only Mercury 2 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) | Mercury 2 | 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 index4 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| MMLU | 68.9% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| LMArena Text: science | Not measured | 1343 | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1363 | Only Mercury 2 measured |
| LMArena Text: business and finance | Not measured | 1349 | Only Mercury 2 measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1035 | Only Mercury 2 measured |
| Design Arena: UI components | Not measured | 996 | Only Mercury 2 measured |
| Design Arena: game dev | Not measured | 983 | Only Mercury 2 measured |
| Design Arena: data viz | Not measured | 1010 | Only Mercury 2 measured |
| Design Arena: 3D | Not measured | 982 | Only Mercury 2 measured |
| Design Arena: all code categories | Not measured | 1021 | Only Mercury 2 measured |
| Design Arena: SVG | Not measured | 997 | Only Mercury 2 measured |
| Design Arena: ASCII art | Not measured | 988 | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | Mercury 2 | Leader |
|---|---|---|---|
| IFBench | Not measured | 69.8% | Only Mercury 2 measured |
| Long context reasoning (AA-LCR) | Not measured | 43.7% | Only Mercury 2 measured |
| WinoGrande | 81.6% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| LMArena Text | Not measured | 1354 | Only Mercury 2 measured |
| LMArena Text: instruction following | Not measured | 1328 | Only Mercury 2 measured |
| LMArena Text: creative writing | Not measured | 1286 | Only Mercury 2 measured |
| LMArena Text: English | Not measured | 1378 | Only Mercury 2 measured |
| LMArena Text: non-English | Not measured | 1330 | Only Mercury 2 measured |
| LMArena Text: Chinese | Not measured | 1414 | Only Mercury 2 measured |
| LMArena Text: Russian | Not measured | 1304 | Only Mercury 2 measured |
| LMArena Text: multi-turn | Not measured | 1357 | Only Mercury 2 measured |
| LMArena Text: longer queries | Not measured | 1329 | Only Mercury 2 measured |
| LMArena Text: writing and language | Not measured | 1300 | Only Mercury 2 measured |
| LMArena Text: entertainment and media | Not measured | 1314 | Only Mercury 2 measured |
| Neither model has a result on the other 34 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
Mercury 2 costs less
Repository review
50K input + 3K output tokens
Mercury 2 costs less
Agent loop
200K input + 10K output tokens
Mercury 2 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) | Inception Mercury 2 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | January 25, 2024 | March 4, 2026 |
| Context window | 4K | 128K |
| Input $/Mtok | $1.00 | $0.25 |
| Output $/Mtok | $2.00 | $0.75 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo (older v0613) better than Mercury 2 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 Mercury 2?
GPT-3.5 Turbo (older v0613) costs $1.00 per million input tokens and $2.00 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo (older v0613) or Mercury 2?
Mercury 2, with 128K tokens against 4K.
Has any benchmark tested both GPT-3.5 Turbo (older v0613) and Mercury 2?
No benchmark has tested both yet. GPT-3.5 Turbo (older v0613) has results on GSM8K, MMLU and WinoGrande; Mercury 2 on LMArena WebDev, AA Coding Index and SciCode. Compare them on price and context instead. Data as of October 22, 2026.