GPT-3.5 Turbo Instruct vs Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct costs 4.5x less per output token than GPT-3.5 Turbo Instruct ($0.44 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
- $0.44
GPT-3.5 Turbo Instruct or Qwen3 Coder 30B A3B Instruct: 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 Instruct has results on METR time horizons; Qwen3 Coder 30B A3B Instruct on SWE-bench Verified, SWE-bench Lite and LiveCodeBench (Artificial Analysis run). 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 Qwen3 Coder 30B A3B Instruct has a AA Intelligence Index result, 9.6.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3 Coder 30B A3B Instruct has a Design Arena: websites result, 1087.
Directional only
Long documents
Listed context window
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct takes 262K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
GPT-3.5 Turbo Instruct $0.0025, Qwen3 Coder 30B A3B Instruct $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo Instruct not benchmarked, Qwen3 Coder 30B A3B Instruct 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 Instruct $2.00 against Qwen3 Coder 30B A3B Instruct $0.44 per million output tokens, 4.5x apart.
- Context window
- GPT-3.5 Turbo Instruct takes 4K tokens, Qwen3 Coder 30B A3B Instruct 262K.
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 Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 60.4% | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 40.3% | Only Qwen3 Coder 30B A3B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only Qwen3 Coder 30B A3B Instruct 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 Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 9.6 | Only Qwen3 Coder 30B A3B Instruct 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 Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen3 Coder 30B A3B Instruct measured |
| METR time horizons | 21.5% | Not measured | Only GPT-3.5 Turbo Instruct measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 51.6% | Only Qwen3 Coder 30B A3B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.8% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 21 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 29.0 | Only Qwen3 Coder 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 70.6% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-3.5 Turbo Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1087 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: UI components | Not measured | 1044 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: data viz | Not measured | 1085 | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 6 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo Instruct | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | Not measured | 32.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| Long context reasoning (AA-LCR) | Not measured | 32.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 46 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
Qwen3 Coder 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder 30B A3B Instruct 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 Instruct | Qwen3 Coder 30B A3B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 28, 2023 | July 31, 2025 |
| Context window | 4K | 262K |
| Input $/Mtok | $1.50 | $0.11 |
| Output $/Mtok | $2.00 | $0.44 |
| 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 Instruct better than Qwen3 Coder 30B A3B Instruct 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 Instruct or Qwen3 Coder 30B A3B Instruct?
GPT-3.5 Turbo Instruct costs $1.50 per million input tokens and $2.00 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.11 and $0.44. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo Instruct or Qwen3 Coder 30B A3B Instruct?
Qwen3 Coder 30B A3B Instruct, with 262K tokens against 4K.
Has any benchmark tested both GPT-3.5 Turbo Instruct and Qwen3 Coder 30B A3B Instruct?
No benchmark has tested both yet. GPT-3.5 Turbo Instruct has results on METR time horizons; Qwen3 Coder 30B A3B Instruct on SWE-bench Verified, SWE-bench Lite and LiveCodeBench (Artificial Analysis run). Compare them on price and context instead. Data as of October 22, 2026.