MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
中文
Model Comparison · Head to Head

GPT-6 Astra vs DeepSeek-V4-Flash

GPT-6 Astra wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorOpenAI / DeepSeek
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose GPT-6 Astra when coding depth, long-context reliability matter most; choose DeepSeek-V4-Flash when lower cost, lower latency, fine-tuning/ecosystem is the priority.

Choose GPT-6 Astra if you…

  • Best-in-class computer use
  • Frontier research & reasoning
  • Autonomous long-horizon tasks
  • Strongest cybersecurity (gated)
  • Best for: Computer use, Deep research, Cybersecurity

Choose DeepSeek-V4-Flash if you…

  • Rock-bottom price
  • Fast
  • Open source
  • Fit for simple tasks
  • Best for: Ultra-fast response, Low cost, High concurrency
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 26 tracked models.

GPT-6 Astra Higher overall
OpenAI · #1 overall
Overall96
Coding97
Multimodal90
VS
DeepSeek-V4-Flash
DeepSeek · #19 overall
Overall67
Coding65
Multimodal65

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionGPT-6 AstraDeepSeek-V4-FlashVerdict
VendorOpenAI (US)DeepSeek (CN)Different vendors
Released2026.092026.04GPT-6 Astra is newer
Overall (rank)96 · #167 · #19GPT-6 Astra +29
Coding97 · #365 · #20GPT-6 Astra +32
Multimodal90 · #765 · #24GPT-6 Astra +25
Context window1.05M1MGPT-6 Astra larger
Max output128K128KTie
Effective-context9690GPT-6 Astra more reliable
Input $/1M$10$0.14DeepSeek-V4-Flash cheaper
Output $/1M$50$0.28DeepSeek-V4-Flash cheaper
Cache discount50% offnoneGPT-6 Astra deeper
Speed~35 tok/s~85 tok/sDeepSeek-V4-Flash faster
TTFT1.1s0.3sDeepSeek-V4-Flash snappier
Function calling9472GPT-6 Astra ahead
Refusal rate~13%~5%DeepSeek-V4-Flash less restrictive
English9975GPT-6 Astra
Chinese7280DeepSeek-V4-Flash
Modalitiestext, imagetextdifferent coverage
Open weightsNoYesDeepSeek-V4-Flash is open
Fine-tuningNoYes
Free tierNo free API tier; Fast mode delivers up to ~2x throughputDeepSeek App free
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesDeepSeek-V4-Flash

Fields drawn from vendor public documentation and the Modelspectra 26-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

GPT-6 Astra leads the overall aggregate by 29 points (96 vs 67). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while DeepSeek-V4-Flash remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: GPT-6 Astra scores 97 against 65. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-6 Astra needs fewer correction turns; DeepSeek-V4-Flash is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

GPT-6 Astra leads multimodal 90 vs 65. A concrete modality difference: GPT-6 Astra additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

DeepSeek-V4-Flash is faster in interactive use: ~85 tok/s with 0.3s TTFT versus ~35 tok/s with 1.1s TTFT (about 2.4× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1.05M for GPT-6 Astra and 1M for DeepSeek-V4-Flash. Effective-context scores point the same way as window size — GPT-6 Astra is ahead on usable recall (96 vs 90), so prefer it for long-document work where details cannot be missed.

Price & total cost

DeepSeek-V4-Flash is the cheaper API at $0.14/$0.28 versus GPT-6 Astra at $10/$50 per 1M input/output tokens — list input is about 71.4× lower. Cache discounts (GPT-6 Astra 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-6 Astra 99 vs DeepSeek-V4-Flash 75. Chinese: 72 vs 80. For Chinese-language production, DeepSeek-V4-Flash is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: GPT-6 Astra 94 vs DeepSeek-V4-Flash 72, so GPT-6 Astra has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Flash. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthGPT-6 AstraDeepSeek-V4-FlashGap
List priceno cache applied$2,500100M in × $10  +  30M out × $50$22100M in × $0.14  +  30M out × $0.28113.64×gap
With caching90% of inputs cache-hit$2,05090M cached in × $5  +  10M in × $10  +  30M out × $50$22no published cache discount93.18×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose GPT-6 Astra (coding 97 vs 65).
IF you serve real-time users and latency is a product KPI  →  choose DeepSeek-V4-Flash (~85 tok/s, 0.3s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose DeepSeek-V4-Flash ($$0.14/$$0.28 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose GPT-6 Astra (effective context 96 vs 90).
07

Frequently asked questions

Is GPT-6 Astra worth the higher price over DeepSeek-V4-Flash?
At list the input rate is 71.4x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-6 Astra's stronger dimensions protect revenue; for routine volume DeepSeek-V4-Flash is the economical pick.
Which is better for agentic coding?
GPT-6 Astra is decisively stronger for coding (97 vs 65 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; DeepSeek-V4-Flash is fine for routine scripts.
Does GPT-6 Astra's higher refusal rate matter in production?
GPT-6 Astra refuses about 13% of prompts versus 5% for DeepSeek-V4-Flash. In unattended pipelines that means more retries, fallbacks and manual review, raising effective cost and latency even when the token price is lower.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-6 Astra is about $2,050/month and DeepSeek-V4-Flash about $22/month after cache discounts ($2,500 and $22 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-6 Astra (1.05M) and DeepSeek-V4-Flash (1M), but usable recall follows the effective-context score (96 vs 90). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
DeepSeek-V4-Flash is the Chinese model (Chinese score 80, domestic cloud, possible private deployment) while GPT-6 Astra is the global model (Chinese 72, overseas API). Pick by language quality, access path and where data must reside.