DeepSeek V4 Flash Vision Exp vs GPT-3.5 Turbo (older v0613)
DeepSeek V4 Flash Vision Exp costs 1.5x less per output token than GPT-3.5 Turbo (older v0613) ($1.32 vs $2.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 56.4
- Output $/M
- $1.32
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.00
DeepSeek V4 Flash Vision Exp or GPT-3.5 Turbo (older v0613): which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V4 Flash Vision Exp for output tokens 1.5x cheaper ($1.32 vs $2.00 per million) and a larger context window (1.05M against 4K tokens).
No benchmark has tested both yet. DeepSeek V4 Flash Vision Exp has results on LiveBench coding, AA Coding Index and SciCode; GPT-3.5 Turbo (older v0613) on GSM8K, MMLU and WinoGrande. 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 DeepSeek V4 Flash Vision Exp has a AA Intelligence Index result, 34.8.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash Vision Exp has a AA Agentic Index result, 47.5.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp $0.0011, GPT-3.5 Turbo (older v0613) $0.0020 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp not benchmarked, GPT-3.5 Turbo (older v0613) 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
- DeepSeek V4 Flash Vision Exp $1.32 against GPT-3.5 Turbo (older v0613) $2.00 per million output tokens, 1.5x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M tokens, GPT-3.5 Turbo (older v0613) 4K.
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 Index3 boards measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| LiveBench coding | 37.6% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| AA Coding Index | 65.0 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| SciCode | 49.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench research | 69.2% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | 64.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | 39.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| LiveBench reasoning | 85.4% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| GSM8K | Not measured | 46.9% | 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 index1 board measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| MMLU | Not measured | 68.9% | Only GPT-3.5 Turbo (older v0613) measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| LiveBench design | 70.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-3.5 Turbo (older v0613) | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Long context reasoning (AA-LCR) | 81.3% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| WinoGrande | Not measured | 81.6% | Only GPT-3.5 Turbo (older v0613) measured |
| Neither model has a result on the other 45 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
DeepSeek V4 Flash Vision Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash Vision Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash Vision Exp 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 V4 Flash Vision Exp | OpenAI GPT-3.5 Turbo (older v0613) |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2026 | January 25, 2024 |
| Context window | 1.05M | 4K |
| Input $/Mtok | $0.44 | $1.00 |
| Output $/Mtok | $1.32 | $2.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GPT-3.5 Turbo (older v0613) for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash Vision Exp for output tokens 1.5x cheaper ($1.32 vs $2.00 per million) and a larger context window (1.05M against 4K tokens).
Which is cheaper, DeepSeek V4 Flash Vision Exp or GPT-3.5 Turbo (older v0613)?
DeepSeek V4 Flash Vision Exp costs $0.44 per million input tokens and $1.32 per million output tokens; GPT-3.5 Turbo (older v0613) costs $1.00 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GPT-3.5 Turbo (older v0613)?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 4K.
Has any benchmark tested both DeepSeek V4 Flash Vision Exp and GPT-3.5 Turbo (older v0613)?
No benchmark has tested both yet. DeepSeek V4 Flash Vision Exp has results on LiveBench coding, AA Coding Index and SciCode; GPT-3.5 Turbo (older v0613) on GSM8K, MMLU and WinoGrande. Compare them on price and context instead. Data as of October 22, 2026.